Source Code for Module test_suite.system_tests.relax_disp

   1  ############################################################################### 
   2  #                                                                             # 
   3  # Copyright (C) 2006-2016 Edward d'Auvergne                                   # 
   4  # Copyright (C) 2009 Sebastien Morin                                          # 
   5  # Copyright (C) 2013-2014 Troels E. Linnet                                    # 
   6  #                                                                             # 
   7  # This file is part of the program relax (http://www.nmr-relax.com).          # 
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  17  # GNU General Public License for more details.                                # 
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  22  ############################################################################### 
  23   
  24  # Python module imports. 
  25  from os import F_OK, access, getcwd, path, sep 
  26  import copy 
  27  from numpy import array, asarray, average, exp, median, inf, isnan, linspace, log, std, sum, zeros 
  28  from minfx.generic import generic_minimise 
  29  from random import gauss 
  30  import re, math 
  31  from tempfile import mkdtemp, NamedTemporaryFile 
  32   
  33   
  34  # relax module imports. 
  35  from auto_analyses import relax_disp 
  36  from auto_analyses.relax_disp_repeat_cpmg import DIC_KEY_FORMAT, Relax_disp_rep 
  37  from data_store import Relax_data_store; ds = Relax_data_store() 
  38  import dep_check 
  39  from lib.dispersion.variables import EXP_TYPE_CPMG_DQ, EXP_TYPE_CPMG_MQ, EXP_TYPE_CPMG_PROTON_MQ, EXP_TYPE_CPMG_PROTON_SQ, EXP_TYPE_CPMG_SQ, EXP_TYPE_CPMG_ZQ, EXP_TYPE_LIST, EXP_TYPE_R1RHO, MODEL_B14_FULL, MODEL_CR72, MODEL_CR72_FULL, MODEL_DPL94, MODEL_IT99, MODEL_LIST_FULL, MODEL_LM63, MODEL_M61, MODEL_M61B, MODEL_MP05, MODEL_NOREX, MODEL_NS_CPMG_2SITE_3D_FULL, MODEL_NS_CPMG_2SITE_EXPANDED, MODEL_NS_CPMG_2SITE_STAR_FULL, MODEL_NS_R1RHO_2SITE, MODEL_PARAMS, MODEL_R2EFF, MODEL_TP02, MODEL_TAP03 
  40  from lib.errors import RelaxError 
  41  from lib.io import extract_data, get_file_path 
  42  from lib.spectrum.nmrpipe import show_apod_extract, show_apod_rmsd, show_apod_rmsd_dir_to_files, show_apod_rmsd_to_file 
  43  from pipe_control.mol_res_spin import generate_spin_string, return_spin, spin_loop 
  44  from pipe_control.minimise import assemble_scaling_matrix 
  45  from specific_analyses.relax_disp.checks import check_missing_r1 
  46  from specific_analyses.relax_disp.estimate_r2eff import estimate_r2eff 
  47  from specific_analyses.relax_disp.data import average_intensity, check_intensity_errors, generate_r20_key, get_curve_type, has_exponential_exp_type, loop_exp_frq, loop_exp_frq_offset_point, loop_time, return_grace_file_name_ini, return_param_key_from_data, spin_ids_to_containers 
  48  from specific_analyses.relax_disp.data import INTERPOLATE_DISP, INTERPOLATE_OFFSET, X_AXIS_DISP, X_AXIS_W_EFF, X_AXIS_THETA, Y_AXIS_R2_R1RHO, Y_AXIS_R2_EFF 
  49  from specific_analyses.relax_disp.model import models_info, nesting_param 
  50  from specific_analyses.relax_disp.parameters import linear_constraints 
  51  from status import Status; status = Status() 
  52  from target_functions.relax_fit_wrapper import Relax_fit_opt 
  53  from test_suite.system_tests.base_classes import SystemTestCase 
  54   
  55   
  56 -class Relax_disp(SystemTestCase): 
  57      """Class for testing various aspects specific to relaxation dispersion curve-fitting.""" 
  58   
  59 -    def __init__(self, methodName='runTest'): 
  60          """Skip certain tests if the C modules are non-functional. 
  61   
  62          @keyword methodName:    The name of the test. 
  63          @type methodName:       str 
  64          """ 
  65   
  66          # Execute the base class method. 
  67          super(Relax_disp, self).__init__(methodName) 
  68   
  69          # Tests to skip. 
  70          blacklist = [ 
  71              'test_m61b_data_to_m61b' 
  72          ] 
  73          if methodName in blacklist: 
  74              status.skipped_tests.append([methodName, None, self._skip_type]) 
  75   
  76          # Missing module. 
  77          if not dep_check.C_module_exp_fn: 
  78              # The list of tests to skip. 
  79              to_skip = [ 
  80                  "test_bug_atul_srivastava", 
  81                  "test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp", 
  82                  "test_bug_9999_slow_r1rho_r2eff_error_with_mc", 
  83                  "test_estimate_r2eff_err", 
  84                  "test_estimate_r2eff_err_auto", 
  85                  "test_estimate_r2eff_err_methods", 
  86                  "test_finite_value", 
  87                  "test_exp_fit", 
  88                  "test_m61_exp_data_to_m61", 
  89                  "test_r1rho_kjaergaard_auto", 
  90                  "test_r1rho_kjaergaard_auto_check_graphs", 
  91                  "test_r1rho_kjaergaard_man", 
  92                  "test_r1rho_kjaergaard_missing_r1", 
  93                  "test_value_write_calc_rotating_frame_params_auto_analysis" 
  94              ] 
  95   
  96              # Store in the status object. 
  97              if methodName in to_skip: 
  98                  status.skipped_tests.append([methodName, 'Relax curve-fitting C module', self._skip_type]) 
  99   
 100          # If not scipy.optimize.leastsq. 
 101          if not dep_check.scipy_module: 
 102              # The list of tests to skip. 
 103              to_skip = [ 
 104                  "test_estimate_r2eff_err_methods" 
 105              ] 
 106   
 107              # Store in the status object. 
 108              if methodName in to_skip: 
 109                  status.skipped_tests.append([methodName, 'scipy.optimize.leastsq module', self._skip_type]) 
 110   
 111          # If not NMRPipe showApod program in PATH. 
 112          if not dep_check.showApod_software: 
 113              # The list of tests to skip. 
 114              to_skip = [ 
 115                  "test_show_apod_extract", 
 116                  "test_show_apod_rmsd", 
 117                  "test_show_apod_rmsd_to_file", 
 118                  "test_show_apod_rmsd_dir_to_files" 
 119              ] 
 120   
 121              # Store in the status object. 
 122              if methodName in to_skip: 
 123                  status.skipped_tests.append([methodName, 'NMRPipe showApod program', self._skip_type]) 
 124   
 125          # If not matplotlib module 
 126          if not dep_check.matplotlib_module: 
 127              # The list of tests to skip. 
 128              to_skip = [ 
 129                  "test_repeat_cpmg" 
 130              ] 
 131   
 132              # Store in the status object. 
 133              if methodName in to_skip: 
 134                  status.skipped_tests.append([methodName, 'matplotlib module', self._skip_type]) 
 135   
 136   
 137 -    def setUp(self): 
 138          """Set up for all the functional tests.""" 
 139   
 140          # Create the data pipe. 
 141          self.interpreter.pipe.create('relax_disp', 'relax_disp') 
 142   
 143          # Create a temporary directory for dumping files. 
 144          ds.tmpdir = mkdtemp() 
 145          self.tmpdir = ds.tmpdir 
 146   
 147   
 148 -    def setup_bug_22146_unpacking_r2a_r2b_cluster(self, folder=None, model_analyse=None, places = 7): 
 149          """Setup data for the catch of U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered full dispersion models. 
 150   
 151          @keyword folder:            The name of the folder for the test data. 
 152          @type folder:               str 
 153          @keyword model_analyse:     The name of the model which will be tested. 
 154          @type model_analyse:        str 
 155          """ 
 156   
 157          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 158   
 159          # Data. 
 160          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22146_unpacking_r2a_r2b_cluster'+sep+folder 
 161   
 162          ## Experiments 
 163          # Exp 1 
 164          sfrq_1 = 500.0*1E6 
 165          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
 166          time_T2_1 = 0.05 
 167          ncycs_1 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 50] 
 168          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 169          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 170          r2eff_errs_1 = [0.0] * len(ncycs_1) 
 171          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
 172   
 173          sfrq_2 = 600.0*1E6 
 174          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
 175          time_T2_2 = 0.06 
 176          ncycs_2 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 40, 60] 
 177          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 178          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 179          r2eff_errs_2 = [0.0] * len(ncycs_2) 
 180          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
 181   
 182          sfrq_3 = 700.0*1E6 
 183          r20_key_3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_3) 
 184          time_T2_3 = 0.07 
 185          ncycs_3 = [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 50, 70] 
 186          # Here you define the direct R2eff errors (rad/s), as being added or subtracted for the created R2eff point in the corresponding ncyc cpmg frequence. 
 187          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05] 
 188          r2eff_errs_3 = [0.0] * len(ncycs_3) 
 189          exp_3 = [sfrq_3, time_T2_3, ncycs_3, r2eff_errs_3] 
 190   
 191          # Collect all exps 
 192          exps = [exp_1, exp_2, exp_3] 
 193   
 194          R20 = [5.1, 5.2, 5.3, 10.1, 10.2, 10.3, 6.1, 6.2, 6.3, 11.1, 11.2, 11.3, 7.1, 7.2, 7.3, 12.1, 12.2, 12.3, 8.1, 8.2, 8.3, 13.1, 13.2, 13.3] 
 195          dw_arr = [1.0, 2.0, 3.0, 4.0] 
 196          pA_arr = [0.9] 
 197          kex_arr = [1000.] 
 198   
 199          spins = [ 
 200                  ['Ala', 1, 'N', {'r2a': {r20_key_1: R20[0], r20_key_2: R20[1], r20_key_3: R20[2]}, 'r2b': {r20_key_1: R20[3], r20_key_2: R20[4], r20_key_3: R20[5]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[0]}], 
 201                  ['Ala', 2, 'N', {'r2a': {r20_key_1: R20[6], r20_key_2: R20[7], r20_key_3: R20[8]}, 'r2b': {r20_key_1: R20[9], r20_key_2: R20[10], r20_key_3: R20[11]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[1]}], 
 202                  ['Ala', 3, 'N', {'r2a': {r20_key_1: R20[12], r20_key_2: R20[13], r20_key_3: R20[14]}, 'r2b': {r20_key_1: R20[15], r20_key_2: R20[16], r20_key_3: R20[17]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[2]}], 
 203                  ['Ala', 4, 'N', {'r2a': {r20_key_1: R20[18], r20_key_2: R20[19], r20_key_3: R20[20]}, 'r2b': {r20_key_1: R20[21], r20_key_2: R20[22], r20_key_3: R20[23]}, 'kex': kex_arr[0], 'pA': pA_arr[0], 'dw': dw_arr[3]}], 
 204                  ] 
 205   
 206          # Create the data pipe. 
 207          pipe_name = 'base pipe' 
 208          pipe_type = 'relax_disp' 
 209          pipe_bundle = 'relax_disp' 
 210          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type, bundle = pipe_bundle) 
 211   
 212          # Generate the sequence. 
 213          for res_name, res_num, spin_name, params in spins: 
 214              self.interpreter.spin.create(res_name=res_name, res_num=res_num, spin_name=spin_name) 
 215   
 216          # Set isotope 
 217          self.interpreter.spin.isotope('15N', spin_id='@N') 
 218   
 219          # Now loop over the experiments, to set the variables in relax. 
 220          exp_ids = [] 
 221          for exp_i in exps: 
 222              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 223              exp_id = 'CPMG_%3.1f' % (sfrq/1E6) 
 224              exp_ids.append(exp_id) 
 225   
 226              ids = [] 
 227              for ncyc in ncycs: 
 228                  nu_cpmg = ncyc / time_T2 
 229                  cur_id = '%s_%.1f' % (exp_id, nu_cpmg) 
 230                  ids.append(cur_id) 
 231   
 232                  # Set the spectrometer frequency. 
 233                  self.interpreter.spectrometer.frequency(id=cur_id, frq=sfrq) 
 234   
 235                  # Set the experiment type. 
 236                  self.interpreter.relax_disp.exp_type(spectrum_id=cur_id, exp_type=EXP_TYPE_CPMG_SQ) 
 237   
 238                  # Set the relaxation dispersion CPMG constant time delay T (in s). 
 239                  self.interpreter.relax_disp.relax_time(spectrum_id=cur_id, time=time_T2) 
 240   
 241                  # Set the relaxation dispersion CPMG frequencies. 
 242                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=cur_id, cpmg_frq=nu_cpmg) 
 243   
 244          print("\n\nThe experiment IDs are %s." % cdp.spectrum_ids) 
 245   
 246          ### Now do fitting. 
 247          # Change pipe. 
 248   
 249          pipe_name_MODEL = "%s_%s"%(pipe_name, model_analyse) 
 250          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_MODEL, bundle_to = pipe_bundle) 
 251          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 252   
 253          # Now read data in. 
 254          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
 255              exp_id = exp_ids[mi] 
 256              exp_i = exps[mi] 
 257              sfrq, time_T2, ncycs, r2eff_errs = exp_i 
 258   
 259              # Then loop over the spins. 
 260              for res_name, res_num, spin_name, params in spins: 
 261                  cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 262   
 263                  # Define file name 
 264                  file_name = "%s%s.txt" % (exp_id, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
 265   
 266                  # Read in the R2eff file to put into spin structure. 
 267                  self.interpreter.relax_disp.r2eff_read_spin(id=exp_id, spin_id=cur_spin_id, file=file_name, dir=data_path, disp_point_col=1, data_col=2, error_col=3) 
 268   
 269          # Then select model. 
 270          self.interpreter.relax_disp.select_model(model=model_analyse) 
 271   
 272          # Then cluster 
 273          self.interpreter.relax_disp.cluster('model_cluster', ":1-100") 
 274   
 275          # Grid search 
 276          low_arr = R20 + dw_arr + pA_arr + kex_arr 
 277          self.interpreter.minimise.grid_search(lower=low_arr, upper=low_arr, inc=1, constraints=True, verbosity=1) 
 278   
 279          # Then loop over the defined spins and read the parameters. 
 280          for i in range(len(spins)): 
 281              res_name, res_num, spin_name, params = spins[i] 
 282              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
 283              cur_spin = return_spin(cur_spin_id) 
 284   
 285              for mo_param in cur_spin.params: 
 286                  print(mo_param) 
 287                  # The R2 is a dictionary, depending on spectrometer frequency. 
 288                  if isinstance(getattr(cur_spin, mo_param), dict): 
 289                      for key, val in list(getattr(cur_spin, mo_param).items()): 
 290                          should_be = params[mo_param][key] 
 291                          print(cur_spin.model, res_name, cur_spin_id, mo_param, key, float(val), should_be) 
 292                          self.assertAlmostEqual(val, should_be) 
 293                  else: 
 294                      should_be = float(params[mo_param]) 
 295                      val = getattr(cur_spin, mo_param) 
 296                      print(cur_spin.model, res_name, cur_spin_id, mo_param, val, should_be) 
 297                      self.assertAlmostEqual(val, should_be) 
 298   
 299              # Test chi2. 
 300              # At this point the chi-squared value at the solution should be zero, as the relaxation data was created with the same parameter values. 
 301              self.assertAlmostEqual(cur_spin.chi2, 0.0, places = places) 
 302   
 303   
 304 -    def setup_r1rho_kjaergaard(self, cluster_ids=[], read_R1=True): 
 305          """Set up the data for the test_r1rho_kjaergaard_*() system tests.""" 
 306   
 307          # The path to the data files. 
 308          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 309   
 310          # Set pipe name, bundle and type. 
 311          ds.pipe_name = 'base pipe' 
 312          ds.pipe_bundle = 'relax_disp' 
 313          ds.pipe_type = 'relax_disp' 
 314   
 315          # Create the data pipe. 
 316          self.interpreter.pipe.create(pipe_name=ds.pipe_name, bundle=ds.pipe_bundle, pipe_type=ds.pipe_type) 
 317   
 318          # Read the spins. 
 319          self.interpreter.spectrum.read_spins(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 320   
 321          # Name the isotope for field strength scaling. 
 322          self.interpreter.spin.isotope(isotope='15N') 
 323   
 324          # Set number of experiments to be used. 
 325          NR_exp = 70 
 326   
 327          # Load the experiments settings file. 
 328          expfile = open(data_path+sep+'exp_parameters_sort.txt', 'r') 
 329          expfileslines = expfile.readlines()[:NR_exp] 
 330          expfile.close() 
 331   
 332          # In MHz 
 333          yOBS = 81.050 
 334          # In ppm 
 335          yCAR = 118.078 
 336          centerPPM_N15 = yCAR 
 337   
 338          ## Read the chemical shift data. 
 339          self.interpreter.chemical_shift.read(file='1_0_46_0_max_standard.ser', dir=data_path+sep+'peak_lists') 
 340   
 341          # The lock power to field, has been found in an calibration experiment. 
 342          spin_lock_field_strengths_Hz = {'35': 431.0, '39': 651.2, '41': 800.5, '43': 984.0, '46': 1341.11, '48': 1648.5} 
 343   
 344          # Apply spectra settings. 
 345          # Count settings 
 346          j = 0 
 347          for i in range(len(expfileslines)): 
 348              line = expfileslines[i] 
 349              if line[0] == "#": 
 350                  continue 
 351              else: 
 352                  # DIRN I deltadof2 dpwr2slock ncyc trim ss sfrq 
 353                  DIRN = line.split()[0] 
 354                  I = int(line.split()[1]) 
 355                  deltadof2 = line.split()[2] 
 356                  dpwr2slock = line.split()[3] 
 357                  ncyc = int(line.split()[4]) 
 358                  trim = float(line.split()[5]) 
 359                  ss = int(line.split()[6]) 
 360                  set_sfrq = float(line.split()[7]) 
 361                  apod_rmsd = float(line.split()[8]) 
 362                  spin_lock_field_strength = spin_lock_field_strengths_Hz[dpwr2slock] 
 363   
 364                  # Calculate spin_lock time 
 365                  time_sl = 2*ncyc*trim 
 366   
 367                  # Define file name for peak list. 
 368                  FNAME = "%s_%s_%s_%s_max_standard.ser"%(I, deltadof2, dpwr2slock, ncyc) 
 369                  sp_id = "%s_%s_%s_%s"%(I, deltadof2, dpwr2slock, ncyc) 
 370   
 371                  # Load the peak intensities. 
 372                  self.interpreter.spectrum.read_intensities(file=FNAME, dir=data_path+sep+'peak_lists', spectrum_id=sp_id, int_method='height') 
 373   
 374                  # Set the peak intensity errors, as defined as the baseplane RMSD. 
 375                  self.interpreter.spectrum.baseplane_rmsd(error=apod_rmsd, spectrum_id=sp_id) 
 376   
 377                  # Set the relaxation dispersion experiment type. 
 378                  self.interpreter.relax_disp.exp_type(spectrum_id=sp_id, exp_type='R1rho') 
 379   
 380                  # Set The spin-lock field strength, nu1, in Hz 
 381                  self.interpreter.relax_disp.spin_lock_field(spectrum_id=sp_id, field=spin_lock_field_strength) 
 382   
 383                  # Calculating the spin-lock offset in ppm, from offsets values provided in Hz. 
 384                  frq_N15_Hz = yOBS * 1E6 
 385                  offset_ppm_N15 = float(deltadof2) / frq_N15_Hz * 1E6 
 386                  omega_rf_ppm = centerPPM_N15 + offset_ppm_N15 
 387   
 388                  # Set The spin-lock offset, omega_rf, in ppm. 
 389                  self.interpreter.relax_disp.spin_lock_offset(spectrum_id=sp_id, offset=omega_rf_ppm) 
 390   
 391                  # Set the relaxation times (in s). 
 392                  self.interpreter.relax_disp.relax_time(spectrum_id=sp_id, time=time_sl) 
 393   
 394                  # Set the spectrometer frequency. 
 395                  self.interpreter.spectrometer.frequency(id=sp_id, frq=set_sfrq, units='MHz') 
 396   
 397                  # Add to counter 
 398                  j += 1 
 399   
 400   
 401          print("Testing the number of settings") 
 402          print("Number of settings iterations is: %s. Number of cdp.exp_type is: %s"%(i, len(cdp.exp_type))) 
 403          self.assertEqual(70, len(expfileslines)) 
 404          self.assertEqual(69, j) 
 405          self.assertEqual(69, len(cdp.exp_type)) 
 406   
 407          # Cluster spins 
 408          for curspin in cluster_ids: 
 409              print("Adding spin %s to cluster"%curspin) 
 410              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
 411   
 412          # De-select for analysis those spins who have not been clustered 
 413          for free_spin in cdp.clustering['free spins']: 
 414              print("Deselecting free spin %s"%free_spin) 
 415              self.interpreter.deselect.spin(spin_id=free_spin, change_all=False) 
 416   
 417   
 418          #Paper         reference values 
 419          #              Resi   Resn         R1_rad_s   R1err_rad_s   R2_rad_s   R2err_rad_s   kEX_rad_s      kEXerr_rad_s  phi_rad2_s2     phierr_rad2_s2    phi_ppm2         phierr_ppm2 
 420          # Scaling rad2_s2 to ppm2: scaling_rad2_s2 = frequency_to_ppm(frq=1/(2*pi), B0=cdp.spectrometer_frq_list[0], isotope='15N')**2 = 3.85167990165e-06 
 421          ds.ref = dict() 
 422          ds.ref[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 423          ds.ref[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 424          ds.ref[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 425          ds.ref[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 426          ds.ref[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 427          ds.ref[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 428          ds.ref[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 429          ds.ref[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 430          ds.ref[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 431          ds.ref[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 432          ds.ref[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 433          ds.ref[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 434          ds.ref[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 435          ds.ref[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 436          ds.ref[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 437   
 438          ds.guess = dict() 
 439          ds.guess[':13@N'] = [13,   'L13N-HN',   1.32394,   0.14687,      8.16007,   1.01237,      13193.82986,   2307.09152,   58703.06446,    22413.09854,      0.2261054135,    0.0863280812] 
 440          ds.guess[':15@N'] = [15,   'R15N-HN',   1.34428,   0.14056,      7.83256,   0.67559,      13193.82986,   2307.09152,   28688.33492,    13480.72253,      0.110498283,     0.051923428] 
 441          ds.guess[':16@N'] = [16,   'T16N-HN',   1.71514,   0.13651,      17.44216,  0.98583,      13193.82986,   2307.09152,   57356.77617,    21892.44205,      0.220919942,     0.084322679] 
 442          ds.guess[':25@N'] = [25,   'Q25N-HN',   1.82412,   0.15809,      9.09447,   2.09215,      13193.82986,   2307.09152,   143111.13431,   49535.80302,      0.5512182797,    0.1907960569] 
 443          ds.guess[':26@N'] = [26,   'Q26N-HN',   1.45746,   0.14127,      10.22801,  0.67116,      13193.82986,   2307.09152,   28187.06876,    13359.01615,      0.1085675662,    0.051454654] 
 444          ds.guess[':28@N'] = [28,   'Q28N-HN',   1.48095,   0.14231,      10.33552,  0.691,        13193.82986,   2307.09152,   30088.0686,     13920.25654,      0.1158896091,    0.0536163723] 
 445          ds.guess[':39@N'] = [39,   'L39N-HN',   1.46094,   0.14514,      8.02194,   0.84649,      13193.82986,   2307.09152,   44130.18538,    18104.55064,      0.1699753481,    0.0697329338] 
 446          ds.guess[':40@N'] = [40,   'M40N-HN',   1.21381,   0.14035,      12.19112,  0.81418,      13193.82986,   2307.09152,   41834.90493,    17319.92156,      0.1611346625,    0.0667107938] 
 447          ds.guess[':41@N'] = [41,   'A41N-HN',   1.29296,   0.14286,      9.29941,   0.66246,      13193.82986,   2307.09152,   26694.8921,     13080.66782,      0.1028201794,    0.0503825453] 
 448          ds.guess[':43@N'] = [43,   'F43N-HN',   1.33626,   0.14352,      12.73816,  1.17386,      13193.82986,   2307.09152,   70347.63797,    26648.30524,      0.2709565833,    0.1026407417] 
 449          ds.guess[':44@N'] = [44,   'I44N-HN',   1.28487,   0.1462,       12.70158,  1.52079,      13193.82986,   2307.09152,   95616.20461,    35307.79817,      0.3682830136,    0.1359943366] 
 450          ds.guess[':45@N'] = [45,   'K45N-HN',   1.59227,   0.14591,      9.54457,   0.95596,      13193.82986,   2307.09152,   53849.7826,     21009.89973,      0.2074121253,    0.0809234085] 
 451          ds.guess[':49@N'] = [49,   'A49N-HN',   1.38521,   0.14148,      4.44842,   0.88647,      13193.82986,   2307.09152,   40686.65286,    18501.20774,      0.1567119631,    0.07126073] 
 452          ds.guess[':52@N'] = [52,   'V52N-HN',   1.57531,   0.15042,      6.51945,   1.43418,      13193.82986,   2307.09152,   93499.92172,    33233.23039,      0.3601317693,    0.1280037656] 
 453          ds.guess[':53@N'] = [53,   'A53N-HN',   1.27214,   0.13823,      4.0705,    0.85485,      13193.82986,   2307.09152,   34856.18636,    17505.02393,      0.1342548725,    0.0674237488] 
 454   
 455          # Assign guess values. 
 456          for spin, spin_id in spin_loop(return_id=True): 
 457              if spin_id in cluster_ids: 
 458                  print("spin_id %s in cluster ids"%(spin_id)) 
 459                  spin.kex = ds.guess[spin_id][6] 
 460                  spin.phi_ex = ds.guess[spin_id][10] 
 461              else: 
 462                  print("spin_id %s NOT in cluster ids"%(spin_id)) 
 463   
 464          if read_R1: 
 465              # Read the R1 data 
 466              self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
 467   
 468   
 469 -    def setup_hansen_cpmg_data(self, model=None): 
 470          """Set up the data for the test_hansen_cpmg_data_*() system tests. 
 471   
 472          @keyword model: The name of the model which will be tested. 
 473          @type model:    str 
 474          """ 
 475   
 476          # Create the data pipe and load the base data. 
 477          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
 478          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 479          self.interpreter.results.read(data_path+sep+'base_pipe') 
 480          self.interpreter.deselect.spin(':4') 
 481   
 482          # Set the nuclear isotope data. 
 483          self.interpreter.spin.isotope('15N') 
 484   
 485          # Create the R2eff data pipe and load the results. 
 486          self.interpreter.pipe.create(pipe_name='R2eff - relax_disp', pipe_type='relax_disp') 
 487          self.interpreter.pipe.switch(pipe_name='R2eff - relax_disp') 
 488          self.interpreter.results.read(data_path+sep+'r2eff_pipe') 
 489          self.interpreter.deselect.spin(':4') 
 490   
 491          # The model data pipe. 
 492          pipe_name = "%s - relax_disp" % model 
 493          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 494          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 495   
 496          # Set the model. 
 497          self.interpreter.relax_disp.select_model(model=model) 
 498   
 499          # Copy the data. 
 500          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to=pipe_name, param='r2eff') 
 501   
 502   
 503 -    def setup_kteilum_fmpoulsen_makke_cpmg_data(self, model=None, expfolder=None): 
 504          """Set up the data for the test_kteilum_fmpoulsen_makke_cpmg_data_*() system tests. 
 505   
 506          @keyword model: The name of the model which will be tested. 
 507          @type model:    str 
 508          """ 
 509   
 510          # Create the data pipe and load the base data. 
 511          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder 
 512          self.interpreter.pipe.create(pipe_name='base pipe', pipe_type='relax_disp') 
 513          self.interpreter.results.read(data_path+sep+'ini_setup_trunc') 
 514   
 515          # Create the R2eff data pipe and load the results. 
 516          self.interpreter.pipe.create(pipe_name='R2eff', pipe_type='relax_disp') 
 517          self.interpreter.pipe.switch(pipe_name='R2eff') 
 518          self.interpreter.results.read(data_path+sep+'r2eff_pipe_trunc') 
 519   
 520          # The model data pipe. 
 521          pipe_name = "%s - relax_disp" % model 
 522          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 523          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 524   
 525          # Set the model. 
 526          self.interpreter.relax_disp.select_model(model=model) 
 527   
 528          # Copy the data. 
 529          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 530   
 531   
 532 -    def setup_korzhnev_2005_data(self, data_list=[]): 
 533          """Set up the data for the test_korzhnev_2005_data_*() system tests using the 'NS MMQ 2-site' model. 
 534   
 535          This loads the proton-heteronuclear SQ, ZQ, DQ, and MQ (MMQ) data from: 
 536   
 537              - Dmitry M. Korzhnev, Philipp Neudecker, Anthony Mittermaier, Vladislav Yu. Orekhov, and Lewis E. Kay (2005)  Multiple-site exchange in proteins studied with a suite of six NMR relaxation dispersion experiments: An application to the folding of a Fyn SH3 domain mutant.  127, 15602-15611 (U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}). 
 538   
 539          It consists of the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
 540   
 541   
 542          @keyword data_list: The list of data to load.  It can contain 'SQ', '1H SQ', 'ZQ', 'DQ', 'MQ', and '1H MQ'. 
 543          @type data_list:    list of str 
 544          """ 
 545   
 546          # Create the data pipe and load the base data. 
 547          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
 548          self.interpreter.pipe.create(pipe_name='Korzhnev et al., 2005', pipe_type='relax_disp') 
 549   
 550          # Create the spin system. 
 551          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
 552          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
 553          self.interpreter.spin.element('H', spin_id='@H') 
 554          self.interpreter.spin.element('N', spin_id='@N') 
 555          self.interpreter.spin.isotope('1H', spin_id='@H') 
 556          self.interpreter.spin.isotope('15N', spin_id='@N') 
 557   
 558          # Define the magnetic dipole-dipole relaxation interaction. 
 559          self.interpreter.interatom.define(spin_id1=':9@N', spin_id2=':9@H', direct_bond=True) 
 560   
 561          # The spectral data - experiment ID, R2eff file name, experiment type, spin ID string, spectrometer frequency in Hertz, relaxation time. 
 562          data = [ 
 563              ['1H SQ', '1H_SQ_CPMG_500_MHz',  'hs_500.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 500e6, 0.03], 
 564              ['1H SQ', '1H_SQ_CPMG_600_MHz',  'hs_600.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 600e6, 0.03], 
 565              ['1H SQ', '1H_SQ_CPMG_800_MHz',  'hs_800.res', EXP_TYPE_CPMG_PROTON_SQ, ':9@H', 800e6, 0.03], 
 566              ['SQ',    '15N_SQ_CPMG_500_MHz', 'ns_500.res', EXP_TYPE_CPMG_SQ,        ':9@N', 500e6, 0.04], 
 567              ['SQ',    '15N_SQ_CPMG_600_MHz', 'ns_600.res', EXP_TYPE_CPMG_SQ,        ':9@N', 600e6, 0.04], 
 568              ['SQ',    '15N_SQ_CPMG_800_MHz', 'ns_800.res', EXP_TYPE_CPMG_SQ,        ':9@N', 800e6, 0.04], 
 569              ['DQ',    '15N_DQ_CPMG_500_MHz', 'dq_500.res', EXP_TYPE_CPMG_DQ,        ':9@N', 500e6, 0.03], 
 570              ['DQ',    '15N_DQ_CPMG_600_MHz', 'dq_600.res', EXP_TYPE_CPMG_DQ,        ':9@N', 600e6, 0.03], 
 571              ['DQ',    '15N_DQ_CPMG_800_MHz', 'dq_800.res', EXP_TYPE_CPMG_DQ,        ':9@N', 800e6, 0.03], 
 572              ['ZQ',    '15N_ZQ_CPMG_500_MHz', 'zq_500.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 500e6, 0.03], 
 573              ['ZQ',    '15N_ZQ_CPMG_600_MHz', 'zq_600.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 600e6, 0.03], 
 574              ['ZQ',    '15N_ZQ_CPMG_800_MHz', 'zq_800.res', EXP_TYPE_CPMG_ZQ,        ':9@N', 800e6, 0.03], 
 575              ['1H MQ', '1H_MQ_CPMG_500_MHz',  'hm_500.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 500e6, 0.02], 
 576              ['1H MQ', '1H_MQ_CPMG_600_MHz',  'hm_600.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 600e6, 0.02], 
 577              ['1H MQ', '1H_MQ_CPMG_800_MHz',  'hm_800.res', EXP_TYPE_CPMG_PROTON_MQ, ':9@H', 800e6, 0.02], 
 578              ['MQ',    '15N_MQ_CPMG_500_MHz', 'nm_500.res', EXP_TYPE_CPMG_MQ,        ':9@N', 500e6, 0.02], 
 579              ['MQ',    '15N_MQ_CPMG_600_MHz', 'nm_600.res', EXP_TYPE_CPMG_MQ,        ':9@N', 600e6, 0.02], 
 580              ['MQ',    '15N_MQ_CPMG_800_MHz', 'nm_800.res', EXP_TYPE_CPMG_MQ,        ':9@N', 800e6, 0.02] 
 581          ] 
 582          cpmg_frqs_1h_sq = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
 583          cpmg_frqs_sq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 584          cpmg_frqs_dq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 585          cpmg_frqs_zq = [33.0, 67.0, 133.0, 200.0, 267.0, 333.0, 400.0, 467.0, 533.0, 667.0, 800.0, 933.0, 1067.0] 
 586          cpmg_frqs_1h_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 1000.0, 1500.0, 2000.0, 2500.0] 
 587          cpmg_frqs_mq = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
 588   
 589          # Loop over the files, reading in the data. 
 590          for data_type, id, file, exp_type, spin_id, H_frq, relax_time in data: 
 591              # Skip undesired data. 
 592              if data_type not in data_list: 
 593                  continue 
 594   
 595              # Alias the CPMG frequencies. 
 596              if data_type == 'SQ': 
 597                  cpmg_frqs = cpmg_frqs_sq 
 598              elif data_type == '1H SQ': 
 599                  cpmg_frqs = cpmg_frqs_1h_sq 
 600              elif data_type == 'DQ': 
 601                  cpmg_frqs = cpmg_frqs_dq 
 602              elif data_type == 'ZQ': 
 603                  cpmg_frqs = cpmg_frqs_zq 
 604              elif data_type == '1H MQ': 
 605                  cpmg_frqs = cpmg_frqs_1h_mq 
 606              elif data_type == 'MQ': 
 607                  cpmg_frqs = cpmg_frqs_mq 
 608   
 609              # Loop over each CPMG frequency. 
 610              for cpmg_frq in cpmg_frqs: 
 611                  # The id. 
 612                  new_id = "%s_%s" % (id, cpmg_frq) 
 613   
 614                  # Set the NMR field strength. 
 615                  self.interpreter.spectrometer.frequency(id=new_id, frq=H_frq) 
 616   
 617                  # Set the relaxation dispersion experiment type. 
 618                  self.interpreter.relax_disp.exp_type(spectrum_id=new_id, exp_type=exp_type) 
 619   
 620                  # Relaxation dispersion CPMG constant time delay T (in s). 
 621                  self.interpreter.relax_disp.relax_time(spectrum_id=new_id, time=relax_time) 
 622   
 623                  # Set the CPMG frequency. 
 624                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=new_id, cpmg_frq=cpmg_frq) 
 625   
 626              # Read the R2eff data. 
 627              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
 628   
 629          # Change the model. 
 630          self.interpreter.relax_disp.select_model('NS MMQ 2-site') 
 631   
 632   
 633 -    def setup_sod1wt_t25(self, pipe_name, pipe_type, pipe_name_r2eff, select_spin_index): 
 634          """Setup of data SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
 635   
 636          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
 637          'SOD1-WT' CPMG data to the CR72 dispersion model. 
 638   
 639          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
 640          Data is for experiment at 25 degree Celcius. 
 641          """ 
 642   
 643          # Create the data pipe and load the base data. 
 644          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'sod1wt_t25' 
 645   
 646          # Set experiment settings. sfrq, time_T2, ncyc 
 647          Exps = [ 
 648          ["600MHz", "Z_A", 599.8908617*1E6, 0.06, [28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 50, 18, 40, 6, 12, 0, 24], ["Z_A1", "Z_A15"] ], 
 649          ["500MHz", "Z_B", 499.862139*1E6, 0.04, [20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0], ["Z_B1", "Z_B18"] ] ] 
 650   
 651          # Create base pipe 
 652          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 653   
 654          # Loop throug experiments 
 655          id_lists = [] 
 656          for folder, key, sfrq, time_T2, ncycs, rep_ncyss in Exps: 
 657              # Read spins 
 658              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 659              self.interpreter.spectrum.read_spins(file="128_FT.ser", dir=data_path+sep+folder) 
 660   
 661              # Make spectrum id list 
 662              id_list = list(key+str(i) for i in range(len(ncycs))) 
 663              id_lists.append(id_list) 
 664   
 665              # Read intensities 
 666              self.interpreter.spectrum.read_intensities(file="128_FT.ser", dir=data_path+sep+folder, int_method='height', spectrum_id=id_list, int_col=list(range(len(id_list))) ) 
 667   
 668              # Loop over experiments 
 669              for i in range(len(ncycs)): 
 670                  ncyc = ncycs[i] 
 671                  vcpmg = ncyc/time_T2 
 672   
 673                  # Test if spectrum is a reference 
 674                  if float(vcpmg) == 0.0: 
 675                      vcpmg = None 
 676                  else: 
 677                      vcpmg = round(float(vcpmg), 3) 
 678   
 679                  # Set current id 
 680                  current_id = id_list[i] 
 681   
 682                  # Set the current experiment type. 
 683                  self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
 684   
 685                  # Set the NMR field strength of the spectrum. 
 686                  self.interpreter.spectrometer.frequency(id=current_id, frq=sfrq, units='Hz') 
 687   
 688                  # Relaxation dispersion CPMG constant time delay T (in s). 
 689                  self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
 690   
 691                  # Set the relaxation dispersion CPMG frequencies. 
 692                  self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
 693   
 694          # Define replicated 
 695          self.interpreter.spectrum.replicated(spectrum_ids=Exps[0][5]) 
 696          self.interpreter.spectrum.replicated(spectrum_ids=Exps[1][5]) 
 697   
 698          # Perform error analysis 
 699          self.interpreter.spectrum.error_analysis(subset=id_lists[0]) 
 700          self.interpreter.spectrum.error_analysis(subset=id_lists[1]) 
 701   
 702          # Define isotope 
 703          self.interpreter.spin.isotope(isotope='15N') 
 704   
 705          ############# 
 706   
 707          # Define the 64 residues which was used for Global fitting 
 708          glob_assn = ["G10N-H", "D11N-H", "Q15N-H", "G16N-H", "G37N-H", "G41N-H", "L42N-H", "H43N-H", "H46N-H", "V47N-H", "E49N-H", 
 709          "E50N-H", "E51N-H", "N53N-H", "T54N-H", "G56N-H", "C57N-H", "T58N-H", "G61N-H", "H63aN-H", "F64aN-H", "N65aN-H", 
 710          "L67N-H", "S68N-H", "K70N-H", "G72N-H", "G73N-H", "K75N-H", "E78N-H", "R79N-H", "H80N-H", "V81N-H", "G82N-H", 
 711          "G85N-H", "N86N-H", "V87N-H", "S102N-H", "V103N-H", "I104N-H", "S105N-H", "A111N-H", "I112N-H", "R115N-H", 
 712          "V118N-H", "E121N-H", "A123N-H", "L126N-H", "G127N-H", "K128N-H", "G129N-H", "G130N-H", "N131N-H", "E133N-H", 
 713          "S134N-H", "T135N-H", "T137N-H", "G138N-H", "N139N-H", "A140N-H", "G141N-H", "S142N-H", "R143N-H", "C146N-H", "G147N-H"] 
 714   
 715          # Test number of global 
 716          self.assertEqual(64, len(glob_assn )) 
 717   
 718          ## Turn assignments into relax spin ids. 
 719          # Define regular expression search 
 720          r = re.compile("([a-zA-Z]+)([0-9]+)([a-zA-Z]+)") 
 721   
 722          # Create list to hold regular expression search 
 723          relax_glob_ids = [] 
 724   
 725          # Loop over assignments 
 726          for assn in glob_assn: 
 727              # Make match for the regular search 
 728              m = r.match(assn) 
 729              # Convert to relax spin string 
 730              relax_string = ":%s@%s"%(m.group(2), m.group(3)) 
 731   
 732              # Save the relax spin string and the regular search 
 733              relax_glob_ids.append([m.group(0), m.group(1), m.group(2), m.group(3), relax_string]) 
 734   
 735          ############# Deselect all spins, and select few spins 
 736   
 737          ## Deselect all spins, and select a few for analysis 
 738          self.interpreter.deselect.all() 
 739   
 740          # Select few spins 
 741          for i in select_spin_index: 
 742              self.interpreter.select.spin(spin_id=relax_glob_ids[i][4], change_all=False) 
 743   
 744          ############## 
 745   
 746          # Prepare for R2eff calculation 
 747          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 748          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 749   
 750          # Select model for points calculation 
 751          MODEL = "R2eff" 
 752          self.interpreter.relax_disp.select_model(model=MODEL) 
 753          # Calculate R2eff values 
 754          self.interpreter.minimise.calculate(verbosity=1) 
 755   
 756   
 757 -    def setup_missing_r1_spins(self): 
 758          """Function for setting up a few spins for the given pipe.""" 
 759   
 760          # Path to file. 
 761          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
 762   
 763          # File with spins. 
 764          file = open(data_path+sep+'R1_fitted_values.txt') 
 765          lines = file.readlines() 
 766          file.close() 
 767   
 768          for i, line in enumerate(lines): 
 769              # Make the string test 
 770              line_split = line.split() 
 771   
 772              if line_split[0] == "#": 
 773                  continue 
 774   
 775              mol_name = line_split[0] 
 776              mol_name = None 
 777              res_num = int(line_split[1]) 
 778              res_name = line_split[2] 
 779              spin_num = line_split[3] 
 780              spin_num = None 
 781              spin_name = line_split[4] 
 782   
 783              # Create the spin. 
 784              self.interpreter.spin.create(spin_name=spin_name, spin_num=spin_num, res_name=res_name, res_num=res_num, mol_name=mol_name) 
 785   
 786   
 787 -    def setup_paul_schanda_nov_2015(self, outdir=None): 
 788          """This setup the truncated private data which was provided by Paul Schanda.""" 
 789   
 790          # Data path. 
 791          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Paul_Schanda_2015_Nov' 
 792          file = data_path + sep + '1_prepare_data.py' 
 793   
 794          # Store the out 
 795          status.outdir = outdir 
 796   
 797          # Run script. 
 798          self.interpreter.script(file=file, dir=None) 
 799   
 800   
 801 -    def setup_tp02_data_to_ns_r1rho_2site(self, clustering=False): 
 802          """Setup data for the test of relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
 803   
 804          # Reset. 
 805          self.interpreter.reset() 
 806   
 807          # Create the data pipe and load the base data. 
 808          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
 809          self.interpreter.state.load(data_path+sep+'r2eff_values') 
 810   
 811          # The model data pipe. 
 812          model = 'NS R1rho 2-site' 
 813          pipe_name = "%s - relax_disp" % model 
 814          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
 815          self.interpreter.pipe.switch(pipe_name=pipe_name) 
 816   
 817          # Set the model. 
 818          self.interpreter.relax_disp.select_model(model=model) 
 819   
 820          # Copy the data. 
 821          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
 822   
 823          # Alias the spins. 
 824          spin1 = cdp.mol[0].res[0].spin[0] 
 825          spin2 = cdp.mol[0].res[1].spin[0] 
 826   
 827          # The R20 keys. 
 828          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
 829          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
 830   
 831          # Set the initial parameter values. 
 832          spin1.r2 = {r20_key1: 9.9963793866185, r20_key2: 15.0056724422684} 
 833          spin1.pA = 0.779782428085762 
 834          spin1.dw = 7.57855284496424 
 835          spin1.kex = 1116.7911285203 
 836          spin2.r2 = {r20_key1: 11.9983346935434, r20_key2: 18.0076097513337} 
 837          spin2.pA = 0.826666229688602 
 838          spin2.dw = 9.5732624231366 
 839          spin2.kex = 1380.46162655657 
 840   
 841          # Test the values when clustering. 
 842          if clustering: 
 843              self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-100") 
 844   
 845          # Low precision optimisation. 
 846          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
 847   
 848          # Printout. 
 849          print("\n\nOptimised parameters:\n") 
 850          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
 851          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
 852          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
 853          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
 854          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
 855          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
 856          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
 857   
 858   
 859 -    def test_baldwin_synthetic(self): 
 860          """Test synthetic data of Andrew J. Baldwin B14 model  whereby the simplification R20A = R20B is assumed. 
 861   
 862          Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
 863   
 864          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>} with R20A, R20B = 2. rad/s. 
 865          """ 
 866   
 867          # The path to the data files. 
 868          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
 869   
 870          # Create pipe 
 871          pipe_name = 'base pipe' 
 872          pipe_type = 'relax_disp' 
 873          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
 874   
 875          # Create base pipe 
 876          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
 877   
 878          # Generate the sequence. 
 879          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
 880   
 881          # Define the isotope. 
 882          self.interpreter.spin.isotope('1H', spin_id='@H') 
 883   
 884          # Build the experiment IDs. 
 885          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
 886          ncycs = [2, 4, 8, 10, 20, 40, 500] 
 887          ids = [] 
 888          for ncyc in ncycs: 
 889              ids.append('CPMG_%s' % ncyc) 
 890   
 891          print("\n\nThe experiment IDs are %s." % ids) 
 892   
 893          # Set up the metadata for the experiments. 
 894          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
 895          sfrq = 200. * 1E6 
 896   
 897          # Total time of CPMG block. 
 898          Trelax = 0.04 
 899   
 900          # First set the 
 901          for i in range(len(ids)): 
 902              id = ids[i] 
 903              # Set the spectrometer frequency. 
 904              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
 905   
 906              # Set the experiment type. 
 907              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
 908   
 909              # Set the relaxation dispersion CPMG constant time delay T (in s). 
 910              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
 911   
 912              # Set the relaxation dispersion CPMG frequencies. 
 913              ncyc = ncycs[i] 
 914              nu_cpmg = ncyc / Trelax 
 915              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
 916   
 917          # Prepare for R2eff reading. 
 918          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
 919          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
 920   
 921          # Try reading the R2eff file. 
 922          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_r2a_eq_r2b_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
 923   
 924          # Check the global data. 
 925          data = [ 
 926              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
 927              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
 928              ['dispersion_points', len(ncycs)], 
 929              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
 930              ['exp_type_list', ['SQ CPMG']], 
 931              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
 932              ['spectrometer_frq_count', 1], 
 933              ['spectrometer_frq_list', [sfrq]], 
 934              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
 935          ] 
 936          for name, value in data: 
 937              # Does it exist? 
 938              self.assert_(hasattr(cdp, name)) 
 939   
 940              # Check the object. 
 941              obj = getattr(cdp, name) 
 942              if not isinstance(data, dict): 
 943                  self.assertEqual(obj, value) 
 944   
 945              # Check the global dictionary data. 
 946              else: 
 947                  for id in ids: 
 948                      self.assertEqual(obj[id], value[id]) 
 949   
 950          # Check the spin data. 
 951          n_data = [ 
 952              [ 50.000000, 10.367900, 0.1], 
 953              [ 100.000000, 10.146849, 0.1], 
 954              [ 200.000000, 9.765987, 0.1], 
 955              [ 250.000000, 9.409789, 0.1], 
 956              [ 500.000000, 5.829819, 0.1], 
 957              [ 1000.000000, 3.191928, 0.1], 
 958              [ 12500.000000, 2.008231, 0.1] 
 959          ] 
 960          for disp_point, value, error in n_data: 
 961              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
 962              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
 963              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
 964   
 965          # Generate r20 key. 
 966          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
 967   
 968          ## Now prepare for MODEL calculation. 
 969          MODEL = "B14" 
 970   
 971          # Change pipe. 
 972          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
 973          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
 974          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
 975   
 976          # Then select model. 
 977          self.interpreter.relax_disp.select_model(model=MODEL) 
 978   
 979          # Store grid and minimisations results. 
 980          grid_results = [] 
 981          mini_results = [] 
 982   
 983          # The grid search size (the number of increments per dimension). 
 984          # If None, use the default values. 
 985          #GRID = None 
 986          GRID = 13 
 987          # Perform Grid Search. 
 988          if GRID: 
 989              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
 990              # This speeds it up considerably. 
 991              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
 992   
 993              # Then do grid search. 
 994              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
 995   
 996              # If no Grid search, set the default values. 
 997          else: 
 998              for param in MODEL_PARAMS[MODEL]: 
 999                  self.interpreter.value.set(param=param, index=None) 
1000                  # Do a grid search, which will store the chi2 value. 
1001              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1002   
1003          # Store result. 
1004          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1005              grid_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1006   
1007          ## Now do minimisation. 
1008          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1009          set_func_tol = 1e-10 
1010          set_max_iter = 1000 
1011          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1012   
1013          # Store result. 
1014          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1015              mini_results.append([spin.r2[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1016   
1017          # Print results. 
1018          for i in range(len(grid_results)): 
1019              g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1020              m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1021              print("GRID %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1022              print("MIN  %s r2=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1023   
1024          # Reference values from Baldwin.py. 
1025          # Exchange rate = k+ + k- (s-1) 
1026          kex = 1000. 
1027          # Fractional population of excited state k+/kex 
1028          pb = 0.01 
1029          # deltaOmega in ppm 
1030          dw_ppm = 2. 
1031          #relaxation rate of ground (s-1) 
1032          R2g = 2. 
1033          #relaxation rate of excited (s-1) 
1034          R2e = 2. 
1035   
1036          # Test the parameters which created the data. 
1037          # This is for the 1H spin. 
1038          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2[r20_key], R2g, 6) 
1039   
1040          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1041          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 8) 
1042          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex, kex, 3) 
1043   
1044   
1045 -    def test_baldwin_synthetic_full(self): 
1046          """Test synthetic data of Andrew J. Baldwin B14 model. Support requst sr #3154 U{https://gna.org/support/index.php?3154}. 
1047   
1048          This uses the synthetic data from paper U{DOI: 10.1016/j.jmr.2014.02.023 <http://dx.doi.org/10.1016/j.jmr.2014.02.023>}. 
1049          """ 
1050   
1051          # The path to the data files. 
1052          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Baldwin_2014' 
1053   
1054          # Create pipe 
1055          pipe_name = 'base pipe' 
1056          pipe_type = 'relax_disp' 
1057          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
1058   
1059          # Create base pipe 
1060          self.interpreter.pipe.create(pipe_name=pipe_name, pipe_type=pipe_type) 
1061   
1062          # Generate the sequence. 
1063          # Generate both a 1H spin, and 15N spin. 
1064          self.interpreter.spin.create(res_name='Ala', res_num=1, spin_name='H') 
1065   
1066          # Define the isotope. 
1067          self.interpreter.spin.isotope('1H', spin_id='@H') 
1068   
1069          # Build the experiment IDs. 
1070          # Number of cpmg cycles (1 cycle = delay/180/delay/delay/180/delay) 
1071          ncycs = [2, 4, 8, 10, 20, 40, 500] 
1072          ids = [] 
1073          for ncyc in ncycs: 
1074              ids.append('CPMG_%s' % ncyc) 
1075   
1076          print("\n\nThe experiment IDs are %s." % ids) 
1077   
1078          # Set up the metadata for the experiments. 
1079          # This value is used in Baldwin.py. It is the 1H Larmor frequency. 
1080          sfrq = 200. * 1E6 
1081   
1082          # Total time of CPMG block. 
1083          Trelax = 0.04 
1084   
1085          # First set the 
1086          for i in range(len(ids)): 
1087              id = ids[i] 
1088              # Set the spectrometer frequency. 
1089              self.interpreter.spectrometer.frequency(id=id, frq=sfrq) 
1090   
1091              # Set the experiment type. 
1092              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
1093   
1094              # Set the relaxation dispersion CPMG constant time delay T (in s). 
1095              self.interpreter.relax_disp.relax_time(spectrum_id=id, time=Trelax) 
1096   
1097              # Set the relaxation dispersion CPMG frequencies. 
1098              ncyc = ncycs[i] 
1099              nu_cpmg = ncyc / Trelax 
1100              self.interpreter.relax_disp.cpmg_setup(spectrum_id=id, cpmg_frq=nu_cpmg) 
1101   
1102          # Prepare for R2eff reading. 
1103          self.interpreter.pipe.copy(pipe_from=pipe_name, pipe_to=pipe_name_r2eff) 
1104          self.interpreter.pipe.switch(pipe_name=pipe_name_r2eff) 
1105   
1106          # Try reading the R2eff file. 
1107          self.interpreter.relax_disp.r2eff_read_spin(id="CPMG", file="test_w_error.out", dir=data_path, spin_id=':1@H', disp_point_col=1, data_col=2, error_col=3) 
1108   
1109          # Check the global data. 
1110          data = [ 
1111              ['cpmg_frqs', {'CPMG_20': 500.0, 'CPMG_10': 250.0, 'CPMG_40': 1000.0, 'CPMG_4': 100.0, 'CPMG_2': 50.0, 'CPMG_500': 12500.0, 'CPMG_8': 200.0}], 
1112              ['cpmg_frqs_list', list(array(ncycs)/Trelax) ], 
1113              ['dispersion_points', len(ncycs)], 
1114              ['exp_type', {'CPMG_20': 'SQ CPMG', 'CPMG_10': 'SQ CPMG', 'CPMG_40': 'SQ CPMG', 'CPMG_4': 'SQ CPMG', 'CPMG_2': 'SQ CPMG', 'CPMG_500': 'SQ CPMG', 'CPMG_8': 'SQ CPMG'}], 
1115              ['exp_type_list', ['SQ CPMG']], 
1116              ['spectrometer_frq', {'CPMG_20': 200000000.0, 'CPMG_10': 200000000.0, 'CPMG_40': 200000000.0, 'CPMG_4': 200000000.0, 'CPMG_2': 200000000.0, 'CPMG_500': 200000000.0, 'CPMG_8': 200000000.0}], 
1117              ['spectrometer_frq_count', 1], 
1118              ['spectrometer_frq_list', [sfrq]], 
1119              ['spectrum_ids', ['CPMG_2', 'CPMG_4', 'CPMG_8', 'CPMG_10', 'CPMG_20', 'CPMG_40', 'CPMG_500']] 
1120          ] 
1121          for name, value in data: 
1122              # Does it exist? 
1123              self.assert_(hasattr(cdp, name)) 
1124   
1125              # Check the object. 
1126              obj = getattr(cdp, name) 
1127              if not isinstance(data, dict): 
1128                  self.assertEqual(obj, value) 
1129   
1130              # Check the global dictionary data. 
1131              else: 
1132                  for id in ids: 
1133                      self.assertEqual(obj[id], value[id]) 
1134   
1135          # Check the spin data. 
1136          n_data = [ 
1137              [ 50.000000, 10.286255, 0.1], 
1138              [ 100.000000, 10.073083, 0.1], 
1139              [ 200.000000, 9.692746, 0.1], 
1140              [ 250.000000, 9.382441, 0.1], 
1141              [ 500.000000, 6.312396, 0.1], 
1142              [ 1000.000000, 3.957029, 0.1], 
1143              [ 12500.000000, 2.880420, 0.1] 
1144          ] 
1145          for disp_point, value, error in n_data: 
1146              id = 'sq_cpmg_200.00000000_0.000_%.3f' % disp_point 
1147              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
1148              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
1149   
1150          # Generate r20 key. 
1151          r20_key = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq) 
1152   
1153          ## Now prepare for MODEL calculation. 
1154          MODEL = "B14 full" 
1155   
1156          # Change pipe. 
1157          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
1158          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
1159          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
1160   
1161          # Then select model. 
1162          self.interpreter.relax_disp.select_model(model=MODEL) 
1163   
1164          # Store grid and minimisations results. 
1165          grid_results = [] 
1166          mini_results = [] 
1167          clust_results = [] 
1168   
1169          # The grid search size (the number of increments per dimension). 
1170          # If None, use the default values. 
1171          #GRID = None 
1172          GRID = 13 
1173          # Perform Grid Search. 
1174          if GRID: 
1175              # Set the R20 parameters in the default grid search using the minimum R2eff value. 
1176              # This speeds it up considerably. 
1177              self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
1178   
1179              # Then do grid search. 
1180              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID, constraints=True, verbosity=1) 
1181   
1182              # If no Grid search, set the default values. 
1183          else: 
1184              for param in MODEL_PARAMS[MODEL]: 
1185                  self.interpreter.value.set(param=param, index=None) 
1186                  # Do a grid search, which will store the chi2 value. 
1187              self.interpreter.minimise.grid_search(lower=None, upper=None, inc=1, constraints=True, verbosity=1) 
1188   
1189          # Store result. 
1190          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1191              grid_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1192   
1193          ## Now do minimisation. 
1194          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
1195          set_func_tol = 1e-11 
1196          set_max_iter = 10000 
1197          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1198   
1199          # Store result. 
1200          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1201              mini_results.append([spin.r2a[r20_key], spin.r2b[r20_key], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
1202   
1203          print("\n# Now print before and after minimisation-\n") 
1204   
1205          # Print results. 
1206          for i in range(len(grid_results)): 
1207              g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
1208              m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
1209              print("GRID %s r2a=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2a, g_r2b, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
1210              print("MIN  %s r2b=%2.4f r2b=%2.4f dw=%1.4f pA=%1.4f kex=%3.4f chi2=%3.4f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2a, m_r2b, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
1211   
1212          # Reference values from Baldwin.py. 
1213          # Exchange rate = k+ + k- (s-1) 
1214          kex = 1000. 
1215          # Fractional population of excited state k+/kex 
1216          pb = 0.01 
1217          # deltaOmega in ppm 
1218          dw_ppm = 2. 
1219          #relaxation rate of ground (s-1) 
1220          R2g = 2. 
1221          #relaxation rate of excited (s-1) 
1222          R2e = 100. 
1223   
1224          # Test the parameters which created the data. 
1225          # This is for the 1H spin. 
1226          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2a[r20_key], R2g, 3) 
1227          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].r2b[r20_key]/100, R2e/100, 3) 
1228   
1229          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].dw, dw_ppm, 6) 
1230          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].pA, 1-pb, 6) 
1231          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].kex/1000, kex/1000, 2) 
1232   
1233   
1234 -    def x_test_bmrb_sub_cpmg(self): 
1235          """U{Task #7858: <https://gna.org/task/?7858>} Make it possible to submit CPMG experiments for BMRB. 
1236          This uses CPMG data from: 
1237              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE. 
1238                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
1239                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, DOI 10.1002/prot.22886 
1240          """ 
1241   
1242          # Define path to data  
1243          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
1244   
1245          # Read data. 
1246          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
1247   
1248          # Set element 
1249          self.interpreter.spin.element(element='N', spin_id=':*@N', force=False) 
1250          #self.interpreter.spin.isotope(isotope='15N', spin_id=':*@N', force=False) 
1251          # Rename molecule from None to 'HEWL' 
1252          self.interpreter.molecule.name(mol_id=None, name='HEWL', force=True) 
1253          self.interpreter.molecule.type(mol_id='#HEWL', type='protein', force=False) 
1254   
1255          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1256              print(spin_id) 
1257              if resn == 'C': 
1258                  print(resi, resn) 
1259   
1260          # Select the thiol state of the system. 
1261          # 'all disulfide bound', 'all free', 'all other bound', 'disulfide and other bound', 'free and disulfide bound', 'free and other bound', 'free disulfide and other bound', 'not available', 'not present', 'not reported', 'unknown' 
1262          self.interpreter.bmrb.thiol_state(state='not reported') 
1263   
1264          # relax_data.temp_calibration(ri_id=None, method=None) 
1265   
1266          # Call display of bmrb. 
1267          self.interpreter.bmrb.display() 
1268   
1269   
1270 -    def test_bug_21081_disp_cluster_fail(self): 
1271          """U{Bug #21081<https://gna.org/bugs/?21081>} catch, the failure of a cluster analysis when spins are deselected.""" 
1272   
1273          # Clear the data store. 
1274          self.interpreter.reset() 
1275   
1276          # Load the state. 
1277          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21081_disp_cluster_fail.bz2' 
1278          self.interpreter.state.load(state, force=True) 
1279   
1280          # Model selection - to catch the failure. 
1281          self.interpreter.model_selection(method='AIC', modsel_pipe='final', bundle='relax_disp', pipes=['No Rex', 'CR72']) 
1282   
1283   
1284 -    def test_bug_21460_disp_cluster_fail(self): 
1285          """U{Bug #21460<https://gna.org/bugs/?21460>} catch, the failure due to a spectrometer frequency having no relaxation data.""" 
1286   
1287          # Clear the data store. 
1288          self.interpreter.reset() 
1289   
1290          # Load the state. 
1291          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states'+sep+'bug_21460_bad_fields.bz2' 
1292          self.interpreter.state.load(state, force=True) 
1293   
1294          # Execute the auto-analysis (fast). 
1295          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1296          relax_disp.Relax_disp.opt_max_iterations = 1000 
1297          relax_disp.Relax_disp(pipe_name="origin - relax_disp (Thu Jan  2 13:46:44 2014)", pipe_bundle="relax_disp (Thu Jan  2 13:46:44 2014)", results_dir=self.tmpdir, models=['R2eff', 'No Rex', 'CR72', 'NS CPMG 2-site expanded'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1298   
1299   
1300 -    def test_bug_21344_sparse_time_spinlock_acquired_r1rho_fail_relax_disp(self): 
1301          """U{Bug #21665<https://gna.org/bugs/?21344>} catch, the failure of an analysis of a sparse acquired R1rho dataset with missing combinations of time and spin-lock field strengths using auto_analysis.""" 
1302   
1303          # Clear the data store. 
1304          self.interpreter.reset() 
1305   
1306          # Load the state. 
1307          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
1308          self.interpreter.state.load(state, force=True) 
1309   
1310          # Execute the auto-analysis (fast). 
1311          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1312          relax_disp.Relax_disp.opt_max_iterations = 1000 
1313          relax_disp.Relax_disp(pipe_name='base pipe', pipe_bundle='relax_disp', results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1314   
1315   
1316 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_calc(self): 
1317          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate().""" 
1318   
1319          # Clear the data store. 
1320          self.interpreter.reset() 
1321   
1322          # Load the state. 
1323          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1324          self.interpreter.state.load(state, force=True) 
1325   
1326          # Run the calculation. 
1327          self.interpreter.minimise.calculate(verbosity=1) 
1328   
1329   
1330 -    def test_bug_21665_cpmg_two_fields_two_delaytimes_fail_relax_disp(self): 
1331          """U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times using auto_analysis.""" 
1332   
1333          # Clear the data store. 
1334          self.interpreter.reset() 
1335   
1336          # Load the state. 
1337          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2' 
1338          self.interpreter.state.load(state, force=True) 
1339   
1340          # Execute the auto-analysis (fast). 
1341          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1342          relax_disp.Relax_disp.opt_max_iterations = 1000 
1343          relax_disp.Relax_disp(pipe_name="compare_128_FT_R2eff", pipe_bundle="cpmg_disp_sod1d90a", results_dir=self.tmpdir, models=['R2eff'], grid_inc=3, mc_sim_num=5, modsel='AIC', pre_run_dir=None, insignificance=1.0, numeric_only=False, mc_sim_all_models=False, eliminate=True) 
1344   
1345   
1346 -    def test_bug_21715_clustered_indexerror(self): 
1347          """Catch U{bug #21715<https://gna.org/bugs/?21715>}, the failure of a clustered auto-analysis due to an IndexError.""" 
1348   
1349          # Clear the data store. 
1350          self.interpreter.reset() 
1351   
1352          # Load the state. 
1353          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'state.bz2' 
1354          self.interpreter.state.load(state, force=True) 
1355   
1356          # Execute the auto-analysis (fast). 
1357          pre_run_dir = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21715_clustered_indexerror'+sep+'non_clustered' 
1358          relax_disp.Relax_disp.opt_func_tol = 1e-5 
1359          relax_disp.Relax_disp.opt_max_iterations = 1000 
1360          relax_disp.Relax_disp(pipe_name='origin - relax_disp (Sun Feb 23 19:36:51 2014)', pipe_bundle='relax_disp (Sun Feb 23 19:36:51 2014)', results_dir=self.tmpdir, models=['R2eff', 'No Rex'], grid_inc=11, mc_sim_num=3, modsel='AIC', pre_run_dir=pre_run_dir, insignificance=1.0, numeric_only=True, mc_sim_all_models=False, eliminate=True) 
1361   
1362   
1363 -    def test_bug_22146_unpacking_r2a_r2b_cluster_B14(self): 
1364          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered B14 full analysis.""" 
1365   
1366          # Base data setup. 
1367          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='B14_full', model_analyse = MODEL_B14_FULL) 
1368   
1369   
1370 -    def test_bug_22146_unpacking_r2a_r2b_cluster_CR72(self): 
1371          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered CR72 full analysis.""" 
1372   
1373          # Base data setup. 
1374          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='CR72_full', model_analyse = MODEL_CR72_FULL) 
1375   
1376   
1377 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_3D(self): 
1378          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE 3D full analysis.""" 
1379   
1380          # Base data setup. 
1381          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_3d_full', model_analyse = MODEL_NS_CPMG_2SITE_3D_FULL) 
1382   
1383   
1384 -    def test_bug_22146_unpacking_r2a_r2b_cluster_NS_STAR(self): 
1385          """Catch U{bug #22146<https://gna.org/bugs/?22146>}, the failure of unpacking R2A and R2B, when performing a clustered NS CPMG 2SITE STAR full analysis.""" 
1386   
1387          # Base data setup. 
1388          self.setup_bug_22146_unpacking_r2a_r2b_cluster(folder='ns_cpmg_2site_star_full', model_analyse = MODEL_NS_CPMG_2SITE_STAR_FULL, places = 4) 
1389   
1390   
1391 -    def test_bug_22477_grace_write_k_AB_mixed_analysis(self): 
1392          """Catch U{bug #22146<https://gna.org/bugs/?22477>}, the failure of issuing: grace.write(x_data_type='res_num', y_data_type=param) for a mixed CPMG analysis.""" 
1393   
1394          # Clear the data store. 
1395          self.interpreter.reset() 
1396   
1397          # Load the state. 
1398          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_22477_grace_write_k_AB_mixed_analysis'+sep+'bug_22477_results.bz2' 
1399          self.interpreter.state.load(state, force=True) 
1400   
1401          param = 'k_AB' 
1402   
1403          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1404              print(spin_id, spin.params) 
1405              if param in spin.params: 
1406                  print(spin_id, spin.k_AB, spin.k_AB_err) 
1407   
1408          # Perform write. 
1409          self.interpreter.grace.write(x_data_type='res_num', y_data_type=param, file='%s.agr'%param, dir=self.tmpdir, force=True) 
1410   
1411   
1412          # Test the header of the value.write  parameter r2. 
1413          param = 'r2' 
1414          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1415   
1416          file = open(self.tmpdir+sep+'%s.out'%param) 
1417          lines = file.readlines() 
1418          file.close() 
1419   
1420          for i, line in enumerate(lines): 
1421              # Make the string test 
1422              line_split = line.split() 
1423              print(line_split) 
1424   
1425              if len(line_split) > 1: 
1426                  # Break at parameter header. 
1427                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1428                      nr_split_header = len(line_split) 
1429                      nr_split_header_i = i 
1430                      break 
1431   
1432          # Call the line after. 
1433          line_split_val = lines[nr_split_header_i + 1].split() 
1434          print(line_split_val) 
1435   
1436          # Assert that the number of columns is equal, plus 1 for "#". 
1437          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1438   
1439          # Test the header of the value.write for parameter r2eff. 
1440          param = 'r2eff' 
1441          self.interpreter.value.write(param=param, file='%s.out'%param, dir=self.tmpdir, force=True) 
1442   
1443          file = open(self.tmpdir+sep+'%s.out'%param) 
1444          lines = file.readlines() 
1445          file.close() 
1446   
1447          for i, line in enumerate(lines): 
1448              # Make the string test 
1449              line_split = line.split() 
1450              print(line_split) 
1451   
1452              if len(line_split) > 1: 
1453                  # Break at parameter header. 
1454                  if line_split[0] == "#" and line_split[1] == 'mol_name': 
1455                      nr_split_header = len(line_split) 
1456                      nr_split_header_i = i 
1457                      break 
1458   
1459          # Call the line after. 
1460          line_split_val = lines[nr_split_header_i + 1].split() 
1461          print(line_split_val) 
1462   
1463          # Assert that the number of columns is equal, plus 1 for "#". 
1464          self.assertEqual(nr_split_header, len(line_split_val) + 1) 
1465   
1466   
1467 -    def test_bug_23186_cluster_error_calc_dw(self): 
1468          """Catch U{bug #23186<https://gna.org/bugs/?23186>}: Error calculation of individual parameter "dw" from Monte-Carlo, is based on first spin.""" 
1469   
1470          # Clear the data store. 
1471          self.interpreter.reset() 
1472   
1473          # Load the state. 
1474          state = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_23186.bz2' 
1475          self.interpreter.state.load(state, force=True) 
1476   
1477          # Dic key to spectrometer frq. 
1478          dickey = 'SQ CPMG - 599.89086220 MHz' 
1479   
1480          # First get the resi 0 array of sim r2a. 
1481          resi_0_r2a = [] 
1482   
1483          # Assign spins 
1484          res0 = cdp.mol[0].res[0].spin[0] 
1485          res1 = cdp.mol[0].res[1].spin[0] 
1486   
1487          print("Chi2 before call to minimise: %3.3f"%res0.chi2) 
1488          self.interpreter.minimise.execute(min_algor='simplex', max_iter=100000, verbosity=0) 
1489          print("Chi2 after call to minimise: %3.3f"%res0.chi2) 
1490   
1491          # Loop over the dics in spin. 
1492          for cdic in res0.r2a_sim: 
1493              resi_0_r2a.append(cdic[dickey]) 
1494   
1495          # Get stats with numpy 
1496          resi_0_r2a_std = std(asarray(resi_0_r2a), ddof=1) 
1497   
1498          # First get the resi 86 array of sim r2a. 
1499          resi_86_r2a = [] 
1500   
1501          # Loop over the dics in spin. 
1502          for cdic in res1.r2a_sim: 
1503              resi_86_r2a.append(cdic[dickey]) 
1504   
1505          # Get stats with numpy 
1506          resi_86_r2a_std = std(asarray(resi_86_r2a), ddof=1) 
1507   
1508          # Then get for dw. 
1509   
1510          # First get the array of sim dw. 
1511          resi_0_dw = res0.dw_sim 
1512          resi_86_dw = res1.dw_sim 
1513   
1514          # Get stats with numpy 
1515          resi_0_dw_std = std(asarray(resi_0_dw), ddof=1) 
1516          resi_86_dw_std = std(asarray(resi_86_dw), ddof=1) 
1517   
1518          # Then get for spin independent parameter. 
1519   
1520          # First get the array of sim dw. 
1521          resi_0_kAB = res0.k_AB_sim 
1522          resi_86_kAB = res1.k_AB_sim 
1523   
1524          # Get stats with numpy 
1525          resi_0_kAB_std = std(asarray(resi_0_kAB), ddof=1) 
1526          resi_86_kAB_std = std(asarray(resi_0_kAB), ddof=1) 
1527   
1528          # Assume they both std of k_AB values are equal 
1529          self.assertEqual(resi_0_kAB_std, resi_86_kAB_std) 
1530   
1531          # Perform error analysis. 
1532          self.interpreter.monte_carlo.error_analysis() 
1533   
1534          # Check values for k_AB. 
1535          self.assertAlmostEqual(resi_0_kAB_std, res0.k_AB_err) 
1536          self.assertAlmostEqual(resi_86_kAB_std, res1.k_AB_err) 
1537   
1538          # Check values for r2a. 
1539          self.assertAlmostEqual(resi_0_r2a_std, res0.r2a_err[dickey]) 
1540          self.assertAlmostEqual(resi_86_r2a_std, res1.r2a_err[dickey]) 
1541   
1542          # Check values for dw. 
1543          self.assertAlmostEqual(resi_0_dw_std, res0.dw_err) 
1544          self.assertAlmostEqual(resi_86_dw_std, res1.dw_err) 
1545   
1546          # The following is for Bug #23619: (https://gna.org/bugs/index.php?23619): Stored chi2 sim values from Monte-Carlo simulations does not equal normal chi2 values. 
1547          # This is to show that this bug is invalid. The "very" different chi2 values stems from r2eff points being back-calculated values rather than original measured values. 
1548   
1549          # Check calculates the same Monte-Carlo chi2 values  
1550          self.interpreter.monte_carlo.setup(number=3) 
1551          self.interpreter.monte_carlo.create_data(method='back_calc') 
1552          self.interpreter.monte_carlo.initial_values() 
1553   
1554          # Assign original data instead of back_calculated error. 
1555          res0.r2eff_sim[0] = copy.copy(res0.r2eff) 
1556          res0.r2eff_sim[1] = copy.copy(res0.r2eff) 
1557          res0.r2eff_sim[2] = copy.copy(res0.r2eff) 
1558          res1.r2eff_sim[0] = copy.copy(res1.r2eff) 
1559          res1.r2eff_sim[1] = copy.copy(res1.r2eff) 
1560          res1.r2eff_sim[2] = copy.copy(res1.r2eff) 
1561   
1562          self.interpreter.minimise.execute(min_algor='simplex', max_iter=100000) 
1563          self.interpreter.monte_carlo.error_analysis() 
1564   
1565          # Get the simulation array and calculate the average 
1566          spin_chi2_mc = res0.chi2 
1567          spin_chi2_mc_sim = res0.chi2_sim 
1568          spin_chi2_mc_sim_ave = average(spin_chi2_mc_sim) 
1569   
1570          print("The chi2 from calculation is: %3.3f"%spin_chi2_mc) 
1571          print("The array with monte-carlo chi2 values is: %s"%spin_chi2_mc_sim) 
1572          print("The average of this array is: %3.3f"%spin_chi2_mc_sim_ave) 
1573   
1574          self.assertAlmostEqual(spin_chi2_mc, spin_chi2_mc_sim_ave, 7) 
1575   
1576   
1577 -    def test_bug_24601_r2eff_missing_data(self): 
1578          """Catch U{bug #24601<https://gna.org/bugs/?24601>}, the failure of optimisation of the 'R2eff' model with missing data.""" 
1579   
1580          # Execute the script. 
1581          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_missing_data.py') 
1582   
1583   
1584 -    def test_bug_9999_slow_r1rho_r2eff_error_with_mc(self): 
1585          """Catch U{bug #9999<https://gna.org/bugs/?9999>}, The slow optimisation of R1rho R2eff error estimation with Monte Carlo simulations.""" 
1586   
1587          # Define path to data  
1588          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
1589   
1590          # Read data. 
1591          self.interpreter.results.read(prev_data_path + sep + 'results')         
1592   
1593          # Now count number 
1594          graph_nr = 1 
1595          for exp_type, frq, offset, point in loop_exp_frq_offset_point(return_indices=False): 
1596              print("\nGraph nr %i" % graph_nr) 
1597              for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
1598                  print(exp_type, frq, offset, point, time) 
1599              graph_nr += 1 
1600   
1601          ## Possibly do an error analysis. 
1602   
1603          # Check if intensity errors have already been calculated by the user. 
1604          precalc = True 
1605          for spin in spin_loop(skip_desel=True): 
1606              # No structure. 
1607              if not hasattr(spin, 'peak_intensity_err'): 
1608                  precalc = False 
1609                  break 
1610   
1611              # Determine if a spectrum ID is missing from the list. 
1612              for id in cdp.spectrum_ids: 
1613                  if id not in spin.peak_intensity_err: 
1614                      precalc = False 
1615                      break 
1616   
1617          # Skip. 
1618          if precalc: 
1619              print("Skipping the error analysis as it has already been performed.") 
1620   
1621          else: 
1622              # Loop over the spectrometer frequencies. 
1623              for frq in loop_frq(): 
1624                  # Generate a list of spectrum IDs matching the frequency. 
1625                  ids = [] 
1626                  for id in cdp.spectrum_ids: 
1627                      # Check that the spectrometer frequency matches. 
1628                      match_frq = True 
1629                      if frq != None and cdp.spectrometer_frq[id] != frq: 
1630                          match_frq = False 
1631   
1632                      # Add the ID. 
1633                      if match_frq: 
1634                          ids.append(id) 
1635   
1636                  # Run the error analysis on the subset. 
1637                  self.interpreter.spectrum.error_analysis(subset=ids) 
1638   
1639          print("has_exponential_exp_type:", has_exponential_exp_type()) 
1640   
1641          model = 'R2eff' 
1642          self.interpreter.relax_disp.select_model(model) 
1643   
1644          for spin, spin_id in spin_loop(return_id=True, skip_desel=True): 
1645              #delattr(spin, 'r2eff') 
1646              #delattr(spin, 'r2eff_err') 
1647              #delattr(spin, 'i0') 
1648              #delattr(spin, 'i0_err') 
1649              setattr(spin, 'r2eff', {}) 
1650              setattr(spin, 'r2eff_err', {}) 
1651              setattr(spin, 'i0', {}) 
1652              setattr(spin, 'i0_err', {}) 
1653   
1654          # Do Grid Search 
1655          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=21, constraints=True, verbosity=1) 
1656   
1657          # Start dic. 
1658          my_dic = {} 
1659   
1660          # Define counter for maximum elements in the numpy array list 
1661          NE = 0 
1662          NS = 1 
1663          NM = 0 
1664          NO = 0 
1665          ND = 0 
1666          NT = 0 
1667   
1668          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1669              # Save to counter. 
1670              if ei > NE: 
1671                  NE = ei 
1672              if mi > NM: 
1673                  NM = mi 
1674              if oi > NO: 
1675                  NO = oi 
1676              if di > ND: 
1677                 ND = di 
1678   
1679              for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1680                  # Save to counter. 
1681                  if ti > NT: 
1682                      NT = ti 
1683   
1684          # Add 1 to counter, since index start from 0. 
1685          NE = NE + 1 
1686          NM = NM + 1  
1687          NO = NO + 1 
1688          ND = ND + 1 
1689          NT = NT + 1 
1690   
1691          # Make data array. 
1692          values_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1693          errors_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1694          times_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1695          struct_arr = zeros([NE, NS, NM, NO, ND, NT]) 
1696          param_key_list = [] 
1697   
1698   
1699          # Loop over each spectrometer frequency and dispersion point. 
1700          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1701              # Add key to dic. 
1702              my_dic[spin_id] = {} 
1703   
1704              # Generate spin string. 
1705              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1706   
1707              # Loop over the parameters. 
1708              #print("Grid optimised parameters for spin: %s" % (spin_string)) 
1709   
1710              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1711                  # Generate the param_key. 
1712                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1713   
1714                  # Append key. 
1715                  param_key_list.append(param_key) 
1716   
1717                  # Add key to dic. 
1718                  my_dic[spin_id][param_key] = {} 
1719   
1720                  # Get the value. 
1721                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1722                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1723   
1724                  # Save to dic. 
1725                  my_dic[spin_id][param_key]['R2eff_value_grid'] = R2eff_value 
1726                  my_dic[spin_id][param_key]['i0_value_grid'] = i0_value 
1727   
1728                  ## Now try do a line of best fit by least squares. 
1729                  # The peak intensities, errors and times. 
1730                  values = [] 
1731                  errors = [] 
1732                  times = [] 
1733                  for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1734                      value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1735                      values.append(value) 
1736   
1737                      error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1738                      errors.append(error) 
1739                      times.append(time) 
1740   
1741                      # Save to numpy arrays. 
1742                      values_arr[ei, 0, mi, oi, di, ti] = value 
1743                      errors_arr[ei, 0, mi, oi, di, ti] = error 
1744                      times_arr[ei, 0, mi, oi, di, ti] = time 
1745                      struct_arr[ei, 0, mi, oi, di, ti] = 1.0 
1746   
1747                  # y= A exp(x * k) 
1748                  # w[i] = ln(y[i]) 
1749                  # int[i] = i0 * exp( - times[i] * r2eff); 
1750                  w = log(array(values)) 
1751                  x = - array(times) 
1752                  n = len(times) 
1753   
1754                  b = (sum(x*w) - 1./n * sum(x) * sum(w) ) / ( sum(x**2) - 1./n * (sum(x))**2 ) 
1755                  a = 1./n * sum(w) - b * 1./n * sum(x) 
1756                  R2eff_est = b 
1757                  i0_est = exp(a) 
1758   
1759                  my_dic[spin_id][param_key]['R2eff_est'] = R2eff_est 
1760                  my_dic[spin_id][param_key]['i0_est'] = i0_est 
1761   
1762                  # Print value. 
1763                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1764                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1765   
1766   
1767          # Do minimisation. 
1768          set_func_tol = 1e-25 
1769          set_max_iter = int(1e7) 
1770          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
1771   
1772          # Loop over each spectrometer frequency and dispersion point. 
1773          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1774              # Generate spin string. 
1775              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1776   
1777              # Loop over the parameters. 
1778              print("Optimised parameters for spin: %s" % (spin_string)) 
1779   
1780              for exp_type, frq, offset, point in loop_exp_frq_offset_point(): 
1781                  # Generate the param_key. 
1782                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1783   
1784                  # Get the value. 
1785                  R2eff_value = getattr(cur_spin, 'r2eff')[param_key] 
1786                  i0_value = getattr(cur_spin, 'i0')[param_key] 
1787   
1788                  # Extract from dic. 
1789                  R2eff_value_grid = my_dic[spin_id][param_key]['R2eff_value_grid'] 
1790                  i0_value_grid = my_dic[spin_id][param_key]['i0_value_grid'] 
1791                  R2eff_est = my_dic[spin_id][param_key]['R2eff_est'] 
1792                  i0_est = my_dic[spin_id][param_key]['i0_est'] 
1793   
1794                  # Print value. 
1795                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'R2eff', "Value : Estimated:", R2eff_value, R2eff_est)) 
1796                  #print("%-10s %-6s %-6s %3.1f : %3.1f" % ("Parameter:", 'i0', "Value: Estimated:", i0_value, i0_est)) 
1797   
1798                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'R2eff', "Grid : Min : Estimated:", R2eff_value_grid, R2eff_value, R2eff_est)) 
1799                  print("%-10s %-6s %-6s %3.1f : %3.1f: %3.1f" % ("Parameter:", 'i0', "Grid : Min : Estimated:", i0_value_grid, i0_value, i0_est)) 
1800   
1801          print(NE, NS, NM, NO, ND, NT) 
1802          for param_key in param_key_list: 
1803              print("        '%s'," % param_key) 
1804          print(values_arr.shape) 
1805   
1806          # Save arrays to profiling. 
1807          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep 
1808          #save(data_path + "values_arr", values_arr) 
1809          #save(data_path + "errors_arr", errors_arr) 
1810          #save(data_path + "times_arr", times_arr) 
1811          #save(data_path + "struct_arr", struct_arr) 
1812   
1813   
1814 -    def test_bug_atul_srivastava(self): 
1815          """Test data from Atul Srivastava.  This is a bug missing raising a Relax Error, since the setup points to a situation where the data 
1816          shows it is exponential fitting, but only one time point is added per file. 
1817   
1818          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1718>}: 
1819          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735>}: 
1820          This follows: U{Thread <http://thread.gmane.org/gmane.science.nmr.relax.user/1735/focus=1736>}: 
1821   
1822          """ 
1823   
1824          # Data path. 
1825          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_Atul_Srivastava' 
1826          file = data_path + sep + 'bug_script.py' 
1827   
1828          # Run script. 
1829          self.interpreter.script(file=file, dir=None) 
1830   
1831          # The grid search size (the number of increments per dimension). 
1832          GRID_INC = 11 
1833   
1834          # Check-data. 
1835          ################# 
1836   
1837          # Loop over spins, to see current setup. 
1838          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1839              print(mol_name, resi, resn, spin_id) 
1840   
1841          # Loop over setup. 
1842          for id in cdp.exp_type: 
1843              print(id, cdp.exp_type[id], cdp.spectrometer_frq[id], cdp.spin_lock_offset[id], cdp.spin_lock_nu1[id]) 
1844   
1845   
1846          # Manual minimisation. 
1847          ################# 
1848          if True: 
1849              # Set the model. 
1850              self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
1851   
1852              # Check if intensity errors have already been calculated. 
1853              check_intensity_errors() 
1854   
1855              # Calculate the R2eff values for the fixed relaxation time period data types. 
1856              if cdp.model_type == MODEL_R2EFF and not has_exponential_exp_type(): 
1857                  self.interpreter.minimise.calculate() 
1858   
1859              # Optimise the model. 
1860              else: 
1861                  constraints = False 
1862                  min_algor = 'Newton' 
1863                  self.assertRaises(RelaxError, self.interpreter.minimise.grid_search, inc=GRID_INC) 
1864                  self.assertRaises(RelaxError, self.interpreter.minimise.execute, min_algor=min_algor, constraints=constraints) 
1865   
1866          # Inspect. 
1867          if False: 
1868              # Loop over attributes. 
1869              par_attr_list = ['r2eff', 'i0'] 
1870   
1871              # Collect the estimation data. 
1872              my_dic = {} 
1873              param_key_list = [] 
1874              est_keys = [] 
1875              est_key = 'grid' 
1876              est_keys.append(est_key) 
1877              spin_id_list = [] 
1878   
1879              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
1880                  # Add key to dic. 
1881                  my_dic[spin_id] = {} 
1882   
1883                  # Add key for estimate. 
1884                  my_dic[spin_id][est_key] = {} 
1885   
1886                  # Add spin key to list. 
1887                  spin_id_list.append(spin_id) 
1888   
1889                  # Generate spin string. 
1890                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
1891   
1892                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
1893                      # Generate the param_key. 
1894                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
1895                      #param_key = generate_r20_key(exp_type=exp_type, frq=frq) 
1896   
1897                      # Append key. 
1898                      param_key_list.append(param_key) 
1899   
1900                      # Add key to dic. 
1901                      my_dic[spin_id][est_key][param_key] = {} 
1902   
1903                      # Get the value. 
1904                      # Loop over err attributes. 
1905                      for par_attr in par_attr_list: 
1906                          if hasattr(cur_spin, par_attr): 
1907                              get_par_attr = getattr(cur_spin, par_attr)[param_key] 
1908                          else: 
1909                              get_par_attr = 0.0 
1910   
1911                          # Save to dic. 
1912                          my_dic[spin_id][est_key][param_key][par_attr] = get_par_attr 
1913   
1914                      # Check number of values. 
1915                      values = [] 
1916                      errors = [] 
1917                      times = [] 
1918                      for time, ti in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point, return_indices=True): 
1919                          value = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, sim_index=None) 
1920                          values.append(value) 
1921   
1922                          error = average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True) 
1923                          errors.append(error) 
1924                          times.append(time) 
1925   
1926                      # Save to dic. 
1927                      my_dic[spin_id][est_key][param_key]['values'] = values 
1928                      my_dic[spin_id][est_key][param_key]['errors'] = errors 
1929                      my_dic[spin_id][est_key][param_key]['times'] = times 
1930   
1931          # Analysis variables. 
1932          ##################### 
1933   
1934          # The dispersion models. 
1935          MODELS = ['R2eff', 'No Rex'] 
1936   
1937          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
1938          MC_NUM = 10 
1939   
1940          # A flag which if True will activate Monte Carlo simulations for all models.  Note this will hugely increase the computation time. 
1941          MC_SIM_ALL_MODELS = False 
1942   
1943          # The results directory. 
1944          RESULTS_DIR = ds.tmpdir 
1945   
1946          # The directory of results of an earlier analysis without clustering. 
1947          PRE_RUN_DIR = None 
1948   
1949          # The model selection technique to use. 
1950          MODSEL = 'AIC' 
1951   
1952          # The flag for only using numeric models in the final model selection. 
1953          NUMERIC_ONLY = False 
1954   
1955          # The R1rho value in rad/s by which to judge insignificance.  If the maximum difference between two points on all dispersion curves for a spin is less than this value, that spin will be deselected. 
1956          INSIGNIFICANCE = 1.0 
1957   
1958          # Auto-analysis execution. 
1959          self.assertRaises(RelaxError, relax_disp.Relax_disp, pipe_name='relax_disp', results_dir=RESULTS_DIR, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, insignificance=INSIGNIFICANCE, numeric_only=NUMERIC_ONLY) 
1960   
1961   
1962 -    def test_bug_negative_intensities_cpmg(self): 
1963          """Test data, where peak intensities are negative in CPMG 
1964   
1965          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
1966          """ 
1967   
1968          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'bug_neg_int_acbp_cpmg_disp_048MGuHCl_40C_041223' 
1969   
1970          # Create the spins 
1971          self.interpreter.spectrum.read_spins(file="peaks_list_max_standard.ser", dir=data_path) 
1972   
1973          # Name the isotope for field strength scaling. 
1974          self.interpreter.spin.isotope(isotope='15N') 
1975   
1976          # Read the spectrum from NMRSeriesTab file. The "auto" will generate spectrum name of form: Z_A{i} 
1977          self.interpreter.spectrum.read_intensities(file="peaks_list_max_standard.ser", dir=data_path, spectrum_id='auto', int_method='height') 
1978   
1979          # Loop over the spectra settings. 
1980          ncycfile=open(data_path + sep + 'ncyc.txt', 'r') 
1981   
1982          # Make empty ncyclist 
1983          ncyclist = [] 
1984   
1985          i = 0 
1986          for line in ncycfile: 
1987              ncyc = line.split()[0] 
1988              time_T2 = float(line.split()[1]) 
1989              vcpmg = line.split()[2] 
1990              set_sfrq = float(line.split()[3]) 
1991              rmsd_err = float(line.split()[4]) 
1992   
1993              # Test if spectrum is a reference 
1994              if float(vcpmg) == 0.0: 
1995                  vcpmg = None 
1996              else: 
1997                  vcpmg = round(float(vcpmg), 3) 
1998   
1999              # Add ncyc to list 
2000              ncyclist.append(int(ncyc)) 
2001   
2002              # Set the current spectrum id 
2003              current_id = "Z_A%s"%(i) 
2004   
2005              # Set the current experiment type. 
2006              self.interpreter.relax_disp.exp_type(spectrum_id=current_id, exp_type='SQ CPMG') 
2007   
2008              # Set the peak intensity errors, as defined as the baseplane RMSD. 
2009              self.interpreter.spectrum.baseplane_rmsd(error=rmsd_err, spectrum_id=current_id) 
2010   
2011              # Set the NMR field strength of the spectrum. 
2012              self.interpreter.spectrometer.frequency(id=current_id, frq=set_sfrq, units='MHz') 
2013   
2014              # Relaxation dispersion CPMG constant time delay T (in s). 
2015              self.interpreter.relax_disp.relax_time(spectrum_id=current_id, time=time_T2) 
2016   
2017              # Set the relaxation dispersion CPMG frequencies. 
2018              self.interpreter.relax_disp.cpmg_setup(spectrum_id=current_id, cpmg_frq=vcpmg) 
2019   
2020              i += 1 
2021   
2022          # Specify the duplicated spectra. 
2023          self.interpreter.spectrum.replicated(spectrum_ids=['Z_A1', 'Z_A15']) 
2024   
2025          # Delete replicate spectrum 
2026          #self.interpreter.spectrum.delete('Z_A15') 
2027   
2028          MODELS = [MODEL_R2EFF, MODEL_NOREX] 
2029          GRID_INC = 5; MC_NUM = 3; MODSEL = 'AIC' 
2030   
2031          results_dir = ds.tmpdir 
2032   
2033          # Execute 
2034          relax_disp.Relax_disp(pipe_name='relax_disp', results_dir=results_dir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
2035   
2036          # Check spin less R2eff points. 
2037          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
2038              # Assert that spin 4, has one less R2eff point, since one of the intensities are negative. 
2039              if spin_id == ':4@N': 
2040                  self.assertEqual(len(cur_spin.r2eff), 14) 
2041              else: 
2042                  self.assertEqual(len(cur_spin.r2eff), 15) 
2043   
2044   
2045 -    def test_check_missing_r1(self): 
2046          """Test of the check_missing_r1() function.""" 
2047   
2048          # Set up some spins. 
2049          self.setup_missing_r1_spins() 
2050   
2051          # Set variables. 
2052          exp_type = 'R1rho' 
2053          frq = 800.1 * 1E6 
2054   
2055          spectrum_id='test' 
2056   
2057          # Set an experiment type to the pipe. 
2058          self.interpreter.relax_disp.exp_type(spectrum_id=spectrum_id, exp_type=exp_type) 
2059   
2060          # Set a frequency to loop through. 
2061          self.interpreter.spectrometer.frequency(id=spectrum_id, frq=frq, units='Hz') 
2062   
2063          # Check R1 for DPL94. 
2064          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
2065          self.assertEqual(check_missing_r1_return, True) 
2066   
2067          # Check R1 for R2eff. 
2068          check_missing_r1_return = check_missing_r1(model=MODEL_R2EFF) 
2069          self.assertEqual(check_missing_r1_return, False) 
2070   
2071          # The path to the data files. 
2072          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
2073   
2074          # Now load some R1 data. 
2075          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
2076   
2077          # Check R1. 
2078          check_missing_r1_return = check_missing_r1(model=MODEL_DPL94) 
2079          self.assertEqual(check_missing_r1_return, False) 
2080   
2081   
2082 -    def test_cpmg_synthetic_b14_to_ns3d_cluster(self): 
2083          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site 3D, for clustered analysis. 
2084   
2085          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2086   
2087          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2088          """ 
2089   
2090          # Reset. 
2091          #self.interpreter.reset() 
2092   
2093          ## Set Experiments. 
2094          model_create = 'B14' 
2095          #model_create = 'NS CPMG 2-site expanded' 
2096          model_analyse = 'NS CPMG 2-site 3D' 
2097   
2098          # Exp 1 
2099          sfrq_1 = 599.8908617*1E6 
2100          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2101          time_T2_1 = 0.06 
2102          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2103          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2104          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2105          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2106   
2107          sfrq_2 = 499.8908617*1E6 
2108          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2109          time_T2_2 = 0.05 
2110          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2111          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2112          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2113          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2114   
2115          # Collect all exps 
2116          exps = [exp_1, exp_2] 
2117   
2118          spins = [ 
2119              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2120              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2121              ] 
2122   
2123          # Collect the data to be used. 
2124          ds.data = [model_create, model_analyse, spins, exps] 
2125   
2126          # The tmp directory. None is the local directory. 
2127          ds.tmpdir = ds.tmpdir 
2128   
2129          # The results directory. None is the local directory. 
2130          #ds.resdir = None 
2131          ds.resdir = ds.tmpdir 
2132   
2133          # Do r20_from_min_r2eff ?. 
2134          ds.r20_from_min_r2eff = True 
2135   
2136          # Remove insignificant level. 
2137          ds.insignificance = 0.0 
2138   
2139          # The grid search size (the number of increments per dimension). 
2140          ds.GRID_INC = None 
2141   
2142          # The do clustering. 
2143          ds.do_cluster = True 
2144   
2145          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2146          # The default value is 1e-25. 
2147          ds.set_func_tol = 1e-1 
2148   
2149          # The maximum number of iterations. 
2150          # The default value is 1e7. 
2151          ds.set_max_iter = 1000 
2152   
2153          # The verbosity level. 
2154          ds.verbosity = 1 
2155   
2156          # The rel_change WARNING level. 
2157          ds.rel_change = 0.05 
2158   
2159          # The plot_curves. 
2160          ds.plot_curves = False 
2161   
2162          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2163          ds.sherekhan_input = False 
2164   
2165          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2166          ds.opendx = False 
2167   
2168          # The set r2eff err. 
2169          ds.r2eff_err = 0.1 
2170   
2171          # The print result info. 
2172          ds.print_res = True 
2173   
2174          # Execute the script. 
2175          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2176   
2177          cur_spins = ds.data[2] 
2178          # Compare results. 
2179          for i in range(len(cur_spins)): 
2180              res_name, res_num, spin_name, params = cur_spins[i] 
2181              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2182              cur_spin = return_spin(cur_spin_id) 
2183   
2184              grid_params = ds.grid_results[i][3] 
2185   
2186              # Extract the clust results. 
2187              min_params = ds.clust_results[i][3] 
2188              # Now read the parameters. 
2189              print("For spin: '%s'"%cur_spin_id) 
2190              for mo_param in cur_spin.params: 
2191                  # The R2 is a dictionary, depending on spectrometer frequency. 
2192                  if isinstance(getattr(cur_spin, mo_param), dict): 
2193                      grid_r2 = grid_params[mo_param] 
2194                      min_r2 = min_params[mo_param] 
2195                      set_r2 = params[mo_param] 
2196                      for key, val in list(set_r2.items()): 
2197                          grid_r2_frq = grid_r2[key] 
2198                          min_r2_frq = min_r2[key] 
2199                          set_r2_frq = set_r2[key] 
2200                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2201                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2202                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2203                          if rel_change > ds.rel_change: 
2204                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2205                              print("###################################") 
2206   
2207                          ## Make test on R2. 
2208                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2209                  else: 
2210                      grid_val = grid_params[mo_param] 
2211                      min_val = min_params[mo_param] 
2212                      set_val = params[mo_param] 
2213                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2214                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2215                      if rel_change > ds.rel_change: 
2216                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2217                          print("###################################") 
2218   
2219                      ## Make test on parameters. 
2220                      if mo_param == 'dw': 
2221                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2222                      elif mo_param == 'kex': 
2223                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2224                      elif mo_param == 'pA': 
2225                          self.assertAlmostEqual(set_val, min_val, 2) 
2226   
2227   
2228 -    def test_cpmg_synthetic_b14_to_ns_star_cluster(self): 
2229          """Test synthetic cpmg data.  Created with B14, analysed with NS CPMG 2site STAR, for clustered analysis. 
2230   
2231          This is part of: U{Task #7807 <https://gna.org/task/index.php?7807>}: Speed-up of dispersion models for Clustered analysis. 
2232   
2233          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2234          """ 
2235   
2236          # Reset. 
2237          #self.interpreter.reset() 
2238   
2239          ## Set Experiments. 
2240          model_create = 'B14' 
2241          #model_create = 'NS CPMG 2-site expanded' 
2242          model_analyse = 'NS CPMG 2-site star' 
2243   
2244          # Exp 1 
2245          sfrq_1 = 599.8908617*1E6 
2246          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2247          time_T2_1 = 0.06 
2248          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2249          #r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2250          r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2251          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2252   
2253          sfrq_2 = 499.8908617*1E6 
2254          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2255          time_T2_2 = 0.05 
2256          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2257          #r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2258          r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2259          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2260   
2261          # Collect all exps 
2262          exps = [exp_1, exp_2] 
2263   
2264          spins = [ 
2265              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.95, 'dw': 2.} ], 
2266              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.95, 'dw': 1.} ] 
2267              ] 
2268   
2269          # Collect the data to be used. 
2270          ds.data = [model_create, model_analyse, spins, exps] 
2271   
2272          # The tmp directory. None is the local directory. 
2273          ds.tmpdir = ds.tmpdir 
2274   
2275          # The results directory. None is the local directory. 
2276          #ds.resdir = None 
2277          ds.resdir = ds.tmpdir 
2278   
2279          # Do r20_from_min_r2eff ?. 
2280          ds.r20_from_min_r2eff = True 
2281   
2282          # Remove insignificant level. 
2283          ds.insignificance = 0.0 
2284   
2285          # The grid search size (the number of increments per dimension). 
2286          ds.GRID_INC = None 
2287   
2288          # The do clustering. 
2289          ds.do_cluster = True 
2290   
2291          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2292          # The default value is 1e-25. 
2293          ds.set_func_tol = 1e-1 
2294   
2295          # The maximum number of iterations. 
2296          # The default value is 1e7. 
2297          ds.set_max_iter = 1000 
2298   
2299          # The verbosity level. 
2300          ds.verbosity = 1 
2301   
2302          # The rel_change WARNING level. 
2303          ds.rel_change = 0.05 
2304   
2305          # The plot_curves. 
2306          ds.plot_curves = False 
2307   
2308          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2309          ds.sherekhan_input = False 
2310   
2311          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2312          ds.opendx = False 
2313   
2314          # The set r2eff err. 
2315          ds.r2eff_err = 0.1 
2316   
2317          # The print result info. 
2318          ds.print_res = True 
2319   
2320          # Execute the script. 
2321          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2322   
2323          cur_spins = ds.data[2] 
2324          # Compare results. 
2325          for i in range(len(cur_spins)): 
2326              res_name, res_num, spin_name, params = cur_spins[i] 
2327              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2328              cur_spin = return_spin(cur_spin_id) 
2329   
2330              grid_params = ds.grid_results[i][3] 
2331   
2332              # Extract the clust results. 
2333              min_params = ds.clust_results[i][3] 
2334              # Now read the parameters. 
2335              print("For spin: '%s'"%cur_spin_id) 
2336              for mo_param in cur_spin.params: 
2337                  # The R2 is a dictionary, depending on spectrometer frequency. 
2338                  if isinstance(getattr(cur_spin, mo_param), dict): 
2339                      grid_r2 = grid_params[mo_param] 
2340                      min_r2 = min_params[mo_param] 
2341                      set_r2 = params[mo_param] 
2342                      for key, val in list(set_r2.items()): 
2343                          grid_r2_frq = grid_r2[key] 
2344                          min_r2_frq = min_r2[key] 
2345                          set_r2_frq = set_r2[key] 
2346                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2347                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2348                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2349                          if rel_change > ds.rel_change: 
2350                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2351                              print("###################################") 
2352   
2353                          ## Make test on R2. 
2354                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2355                  else: 
2356                      grid_val = grid_params[mo_param] 
2357                      min_val = min_params[mo_param] 
2358                      set_val = params[mo_param] 
2359                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2360                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2361                      if rel_change > ds.rel_change: 
2362                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2363                          print("###################################") 
2364   
2365                      ## Make test on parameters. 
2366                      if mo_param == 'dw': 
2367                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2368                      elif mo_param == 'kex': 
2369                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2370                      elif mo_param == 'pA': 
2371                          self.assertAlmostEqual(set_val, min_val, 2) 
2372   
2373   
2374 -    def test_cpmg_synthetic_ns3d_to_cr72(self): 
2375          """Test synthetic cpmg data. 
2376   
2377          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with CR72. 
2378          """ 
2379   
2380          # Reset. 
2381          #self.interpreter.reset() 
2382   
2383          ## Set Experiments. 
2384          model_create = 'NS CPMG 2-site 3D' 
2385          #model_create = 'NS CPMG 2-site expanded' 
2386          model_analyse = 'CR72' 
2387          # Exp 1 
2388          sfrq_1 = 599.8908617*1E6 
2389          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2390          time_T2_1 = 0.06 
2391          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2392          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2393          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2394   
2395          sfrq_2 = 499.8908617*1E6 
2396          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2397          time_T2_2 = 0.05 
2398          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2399          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2400          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2401   
2402          # Collect all exps 
2403          exps = [exp_1, exp_2] 
2404   
2405          spins = [ 
2406              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2407              ] 
2408   
2409          # Collect the data to be used. 
2410          ds.data = [model_create, model_analyse, spins, exps] 
2411   
2412          # The tmp directory. None is the local directory. 
2413          ds.tmpdir = ds.tmpdir 
2414   
2415          # The results directory. None is the local directory. 
2416          #ds.resdir = None 
2417          ds.resdir = ds.tmpdir 
2418   
2419          # Do r20_from_min_r2eff ?. 
2420          ds.r20_from_min_r2eff = True 
2421   
2422          # Remove insignificant level. 
2423          ds.insignificance = 0.0 
2424   
2425          # The grid search size (the number of increments per dimension). 
2426          ds.GRID_INC = 8 
2427   
2428          # The do clustering. 
2429          ds.do_cluster = False 
2430   
2431          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2432          # The default value is 1e-25. 
2433          ds.set_func_tol = 1e-9 
2434   
2435          # The maximum number of iterations. 
2436          # The default value is 1e7. 
2437          ds.set_max_iter = 1000 
2438   
2439          # The verbosity level. 
2440          ds.verbosity = 1 
2441   
2442          # The rel_change WARNING level. 
2443          ds.rel_change = 0.05 
2444   
2445          # The plot_curves. 
2446          ds.plot_curves = False 
2447   
2448          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2449          ds.sherekhan_input = False 
2450   
2451          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2452          ds.opendx = False 
2453   
2454          # The set r2eff err. 
2455          ds.r2eff_err = 0.1 
2456   
2457          # The print result info. 
2458          ds.print_res = False 
2459   
2460          # Execute the script. 
2461          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2462   
2463          cur_spins = ds.data[2] 
2464          # Compare results. 
2465          for i in range(len(cur_spins)): 
2466              res_name, res_num, spin_name, params = cur_spins[i] 
2467              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2468              cur_spin = return_spin(cur_spin_id) 
2469   
2470              grid_params = ds.grid_results[i][3] 
2471              min_params = ds.min_results[i][3] 
2472              # Now read the parameters. 
2473              print("For spin: '%s'"%cur_spin_id) 
2474              for mo_param in cur_spin.params: 
2475                  # The R2 is a dictionary, depending on spectrometer frequency. 
2476                  if isinstance(getattr(cur_spin, mo_param), dict): 
2477                      grid_r2 = grid_params[mo_param] 
2478                      min_r2 = min_params[mo_param] 
2479                      set_r2 = params[mo_param] 
2480                      for key, val in list(set_r2.items()): 
2481                          grid_r2_frq = grid_r2[key] 
2482                          min_r2_frq = min_r2[key] 
2483                          set_r2_frq = set_r2[key] 
2484                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2485                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2486                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2487                          if rel_change > ds.rel_change: 
2488                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2489                              print("###################################") 
2490   
2491                          ## Make test on R2. 
2492                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2493                  else: 
2494                      grid_val = grid_params[mo_param] 
2495                      min_val = min_params[mo_param] 
2496                      set_val = params[mo_param] 
2497                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2498                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2499                      if rel_change > ds.rel_change: 
2500                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2501                          print("###################################") 
2502   
2503                      ## Make test on parameters. 
2504                      if mo_param == 'dw': 
2505                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2506                      elif mo_param == 'kex': 
2507                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2508                      elif mo_param == 'pA': 
2509                          self.assertAlmostEqual(set_val, min_val, 3) 
2510   
2511   
2512 -    def test_cpmg_synthetic_ns3d_to_b14(self): 
2513          """Test synthetic cpmg data. 
2514   
2515          This script will produce synthetic CPMG R2eff values according to the NS CPMG 2-site 3D model, and the fit the data with B14. 
2516          Try to catch bug #22021 U{https://gna.org/bugs/index.php?22021}: Model B14 shows bad fitting to data. 
2517          """ 
2518   
2519          # Reset. 
2520          #self.interpreter.reset() 
2521   
2522          ## Set Experiments. 
2523          model_create = 'NS CPMG 2-site 3D' 
2524          #model_create = 'NS CPMG 2-site expanded' 
2525          model_analyse = 'B14' 
2526          # Exp 1 
2527          sfrq_1 = 599.8908617*1E6 
2528          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2529          time_T2_1 = 0.06 
2530          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2531          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2532          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2533   
2534          sfrq_2 = 499.8908617*1E6 
2535          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2536          time_T2_2 = 0.05 
2537          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2538          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2539          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2540   
2541          # Collect all exps 
2542          exps = [exp_1, exp_2] 
2543   
2544          spins = [ 
2545              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:10.}, 'r2a': {r20_key_1:10., r20_key_2:10.}, 'r2b': {r20_key_1:10., r20_key_2:10.}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ] 
2546              ] 
2547   
2548          # Collect the data to be used. 
2549          ds.data = [model_create, model_analyse, spins, exps] 
2550   
2551          # The tmp directory. None is the local directory. 
2552          ds.tmpdir = ds.tmpdir 
2553   
2554          # The results directory. None is the local directory. 
2555          #ds.resdir = None 
2556          ds.resdir = ds.tmpdir 
2557   
2558          # Do r20_from_min_r2eff ?. 
2559          ds.r20_from_min_r2eff = True 
2560   
2561          # Remove insignificant level. 
2562          ds.insignificance = 0.0 
2563   
2564          # The grid search size (the number of increments per dimension). 
2565          ds.GRID_INC = 8 
2566   
2567          # The do clustering. 
2568          ds.do_cluster = False 
2569   
2570          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2571          # The default value is 1e-25. 
2572          ds.set_func_tol = 1e-9 
2573   
2574          # The maximum number of iterations. 
2575          # The default value is 1e7. 
2576          ds.set_max_iter = 1000 
2577   
2578          # The verbosity level. 
2579          ds.verbosity = 1 
2580   
2581          # The rel_change WARNING level. 
2582          ds.rel_change = 0.05 
2583   
2584          # The plot_curves. 
2585          ds.plot_curves = False 
2586   
2587          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2588          ds.sherekhan_input = False 
2589   
2590          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2591          ds.opendx = False 
2592   
2593          # The set r2eff err. 
2594          ds.r2eff_err = 0.1 
2595   
2596          # The print result info. 
2597          ds.print_res = False 
2598   
2599          # Execute the script. 
2600          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2601   
2602          cur_spins = ds.data[2] 
2603          # Compare results. 
2604          for i in range(len(cur_spins)): 
2605              res_name, res_num, spin_name, params = cur_spins[i] 
2606              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2607              cur_spin = return_spin(cur_spin_id) 
2608   
2609              grid_params = ds.grid_results[i][3] 
2610              min_params = ds.min_results[i][3] 
2611              # Now read the parameters. 
2612              print("For spin: '%s'"%cur_spin_id) 
2613              for mo_param in cur_spin.params: 
2614                  # The R2 is a dictionary, depending on spectrometer frequency. 
2615                  if isinstance(getattr(cur_spin, mo_param), dict): 
2616                      grid_r2 = grid_params[mo_param] 
2617                      min_r2 = min_params[mo_param] 
2618                      set_r2 = params[mo_param] 
2619                      for key, val in list(set_r2.items()): 
2620                          grid_r2_frq = grid_r2[key] 
2621                          min_r2_frq = min_r2[key] 
2622                          set_r2_frq = set_r2[key] 
2623                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2624                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2625                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2626                          if rel_change > ds.rel_change: 
2627                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2628                              print("###################################") 
2629   
2630                          ## Make test on R2. 
2631                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 2) 
2632                  else: 
2633                      grid_val = grid_params[mo_param] 
2634                      min_val = min_params[mo_param] 
2635                      set_val = params[mo_param] 
2636                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2637                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2638                      if rel_change > ds.rel_change: 
2639                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2640                          print("###################################") 
2641   
2642                      ## Make test on parameters. 
2643                      if mo_param == 'dw': 
2644                          self.assertAlmostEqual(set_val/10, min_val/10, 5) 
2645                      elif mo_param == 'kex': 
2646                          self.assertAlmostEqual(set_val/1000, min_val/1000, 5) 
2647                      elif mo_param == 'pA': 
2648                          self.assertAlmostEqual(set_val, min_val, 6) 
2649   
2650   
2651 -    def test_cpmg_synthetic_ns3d_to_cr72_noise_cluster(self): 
2652          """Test synthetic cpmg data. For CR72 with small noise and cluster. 
2653   
2654          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2655          """ 
2656   
2657          # Reset. 
2658          #self.interpreter.reset() 
2659   
2660          ## Set Experiments. 
2661          model_create = 'NS CPMG 2-site 3D' 
2662          #model_create = 'NS CPMG 2-site expanded' 
2663          model_analyse = 'CR72' 
2664   
2665          # Exp 1 
2666          sfrq_1 = 599.8908617*1E6 
2667          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2668          time_T2_1 = 0.06 
2669          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2670          r2eff_errs_1 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2671          #r2eff_errs_1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2672          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_errs_1] 
2673   
2674          sfrq_2 = 499.8908617*1E6 
2675          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2676          time_T2_2 = 0.05 
2677          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2678          r2eff_errs_2 = [0.05, -0.05, 0.05, -0.05, 0.05, -0.05, 0.05, -0.05] 
2679          #r2eff_errs_2 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 
2680          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_errs_2] 
2681   
2682          # Collect all exps 
2683          exps = [exp_1, exp_2] 
2684   
2685          spins = [ 
2686              ['Ala', 1, 'N', {'r2': {r20_key_1:10., r20_key_2:11.5}, 'r2a': {r20_key_1:10., r20_key_2:11.5}, 'r2b': {r20_key_1:10., r20_key_2:11.5}, 'kex': 1000., 'pA': 0.99, 'dw': 2.} ], 
2687              ['Ala', 2, 'N', {'r2': {r20_key_1:13., r20_key_2:14.5}, 'r2a': {r20_key_1:13., r20_key_2:14.5}, 'r2b': {r20_key_1:13., r20_key_2:14.5}, 'kex': 1000., 'pA': 0.99, 'dw': 1.} ] 
2688              ] 
2689   
2690          # Collect the data to be used. 
2691          ds.data = [model_create, model_analyse, spins, exps] 
2692   
2693          # The tmp directory. None is the local directory. 
2694          ds.tmpdir = ds.tmpdir 
2695   
2696          # The results directory. None is the local directory. 
2697          #ds.resdir = None 
2698          ds.resdir = ds.tmpdir 
2699   
2700          # Do r20_from_min_r2eff ?. 
2701          ds.r20_from_min_r2eff = True 
2702   
2703          # Remove insignificant level. 
2704          ds.insignificance = 0.0 
2705   
2706          # The grid search size (the number of increments per dimension). 
2707          ds.GRID_INC = 13 
2708   
2709          # The do clustering. 
2710          ds.do_cluster = True 
2711   
2712          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2713          # The default value is 1e-25. 
2714          ds.set_func_tol = 1e-8 
2715   
2716          # The maximum number of iterations. 
2717          # The default value is 1e7. 
2718          ds.set_max_iter = 10000 
2719   
2720          # The verbosity level. 
2721          ds.verbosity = 1 
2722   
2723          # The rel_change WARNING level. 
2724          ds.rel_change = 0.05 
2725   
2726          # The plot_curves. 
2727          ds.plot_curves = False 
2728   
2729          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2730          ds.sherekhan_input = False 
2731   
2732          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2733          ds.opendx = False 
2734   
2735          # The set r2eff err. 
2736          ds.r2eff_err = 0.1 
2737   
2738          # The print result info. 
2739          ds.print_res = False 
2740   
2741          # Execute the script. 
2742          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2743   
2744          cur_spins = ds.data[2] 
2745          # Compare results. 
2746          for i in range(len(cur_spins)): 
2747              res_name, res_num, spin_name, params = cur_spins[i] 
2748              cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2749              cur_spin = return_spin(cur_spin_id) 
2750   
2751              grid_params = ds.grid_results[i][3] 
2752   
2753              # Extract the clust results. 
2754              min_params = ds.clust_results[i][3] 
2755              # Now read the parameters. 
2756              print("For spin: '%s'"%cur_spin_id) 
2757              for mo_param in cur_spin.params: 
2758                  # The R2 is a dictionary, depending on spectrometer frequency. 
2759                  if isinstance(getattr(cur_spin, mo_param), dict): 
2760                      grid_r2 = grid_params[mo_param] 
2761                      min_r2 = min_params[mo_param] 
2762                      set_r2 = params[mo_param] 
2763                      for key, val in list(set_r2.items()): 
2764                          grid_r2_frq = grid_r2[key] 
2765                          min_r2_frq = min_r2[key] 
2766                          set_r2_frq = set_r2[key] 
2767                          frq = float(key.split(EXP_TYPE_CPMG_SQ+' - ')[-1].split('MHz')[0]) 
2768                          rel_change = math.sqrt( (min_r2_frq - set_r2_frq)**2/(min_r2_frq)**2 ) 
2769                          print("%s %s %s %s %.1f GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, frq, grid_r2_frq, min_r2_frq, set_r2_frq, rel_change) ) 
2770                          if rel_change > ds.rel_change: 
2771                              print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2772                              print("###################################") 
2773   
2774                          ## Make test on R2. 
2775                          self.assertAlmostEqual(set_r2_frq, min_r2_frq, 1) 
2776                  else: 
2777                      grid_val = grid_params[mo_param] 
2778                      min_val = min_params[mo_param] 
2779                      set_val = params[mo_param] 
2780                      rel_change = math.sqrt( (min_val - set_val)**2/(min_val)**2 ) 
2781                      print("%s %s %s %s GRID=%.3f MIN=%.3f SET=%.3f RELC=%.3f"%(cur_spin.model, res_name, cur_spin_id, mo_param, grid_val, min_val, set_val, rel_change) ) 
2782                      if rel_change > ds.rel_change: 
2783                          print("WARNING: rel change level is above %.2f, and is %.4f."%(ds.rel_change, rel_change)) 
2784                          print("###################################") 
2785   
2786                      ## Make test on parameters. 
2787                      if mo_param == 'dw': 
2788                          self.assertAlmostEqual(set_val/10, min_val/10, 1) 
2789                      elif mo_param == 'kex': 
2790                          self.assertAlmostEqual(set_val/1000, min_val/1000, 1) 
2791                      elif mo_param == 'pA': 
2792                          self.assertAlmostEqual(set_val, min_val, 2) 
2793   
2794   
2795 -    def test_cpmg_synthetic_dx_map_points(self): 
2796          """Test synthetic cpmg data, calling the dx.map function with one or two points. 
2797   
2798          This script will produce synthetic CPMG R2eff values according to the selected model, and the fit the selected model. 
2799          """ 
2800   
2801          # Reset. 
2802          #self.interpreter.reset() 
2803   
2804          ## Set Experiments. 
2805          model_create = MODEL_NS_CPMG_2SITE_EXPANDED 
2806          model_analyse = 'CR72' 
2807          # Exp 1 
2808          sfrq_1 = 599.8908617*1E6 
2809          r20_key_1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_1) 
2810          time_T2_1 = 0.06 
2811          ncycs_1 = [2, 4, 8, 10, 20, 30, 40, 60] 
2812          r2eff_err_1 = [0, 0, 0, 0, 0, 0, 0, 0] 
2813          exp_1 = [sfrq_1, time_T2_1, ncycs_1, r2eff_err_1] 
2814   
2815          sfrq_2 = 499.8908617*1E6 
2816          r20_key_2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=sfrq_2) 
2817          time_T2_2 = 0.05 
2818          ncycs_2 = [2, 4, 8, 10, 30, 35, 40, 50] 
2819          r2eff_err_2 = [0, 0, 0, 0, 0, 0, 0, 0] 
2820          exp_2 = [sfrq_2, time_T2_2, ncycs_2, r2eff_err_2] 
2821   
2822          # Collect all exps 
2823          exps = [exp_1, exp_2] 
2824   
2825          spins = [ 
2826              ['Ala', 1, 'N', {'r2': {r20_key_1:2, r20_key_2:2}, 'r2a': {r20_key_1:2, r20_key_2:2}, 'r2b': {r20_key_1:2, r20_key_2:2}, 'kex': 1000, 'pA': 0.99, 'dw': 2} ] 
2827              ] 
2828   
2829          # Collect the data to be used. 
2830          ds.data = [model_create, model_analyse, spins, exps] 
2831   
2832          # The tmp directory. None is the local directory. 
2833          ds.tmpdir = ds.tmpdir 
2834   
2835          # The results directory. None is the local directory. 
2836          #ds.resdir = None 
2837          ds.resdir = ds.tmpdir 
2838   
2839          # Do r20_from_min_r2eff ?. 
2840          ds.r20_from_min_r2eff = True 
2841   
2842          # Remove insignificant level. 
2843          ds.insignificance = 0.0 
2844   
2845          # The grid search size (the number of increments per dimension). 
2846          ds.GRID_INC = None 
2847   
2848          # The do clustering. 
2849          ds.do_cluster = False 
2850   
2851          # The function tolerance.  This is used to terminate minimisation once the function value between iterations is less than the tolerance. 
2852          # The default value is 1e-25. 
2853          ds.set_func_tol = 1e-9 
2854   
2855          # The maximum number of iterations. 
2856          # The default value is 1e7. 
2857          ds.set_max_iter = 1000 
2858   
2859          # The verbosity level. 
2860          ds.verbosity = 1 
2861   
2862          # The rel_change WARNING level. 
2863          ds.rel_change = 0.05 
2864   
2865          # The plot_curves. 
2866          ds.plot_curves = False 
2867   
2868          # The conversion for ShereKhan at http://sherekhan.bionmr.org/. 
2869          ds.sherekhan_input = False 
2870   
2871          # Make a dx map to be opened om OpenDX. To map the hypersurface of chi2, when altering kex, dw and pA. 
2872          ds.opendx = False 
2873   
2874          # The set r2eff err. 
2875          ds.r2eff_err = 0.1 
2876   
2877          # The print result info. 
2878          ds.print_res = False 
2879   
2880          # Execute the script. 
2881          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'cpmg_synthetic.py') 
2882   
2883          # Get the spins. 
2884          cur_spins = ds.data[2] 
2885   
2886          # First switch pipe, since dx.map will go through parameters and end up a "bad" place. :-) 
2887          ds.pipe_name_MODEL_MAP = "%s_%s_map"%(ds.pipe_name, model_analyse) 
2888          self.interpreter.pipe.copy(pipe_from=ds.pipe_name, pipe_to=ds.pipe_name_MODEL_MAP, bundle_to = ds.pipe_bundle) 
2889          self.interpreter.pipe.switch(pipe_name=ds.pipe_name_MODEL_MAP) 
2890   
2891          # Copy R2eff, but not the original parameters 
2892          self.interpreter.value.copy(pipe_from=ds.pipe_name_r2eff, pipe_to=ds.pipe_name_MODEL_MAP, param='r2eff') 
2893   
2894          # Then select model. 
2895          self.interpreter.relax_disp.select_model(model=model_analyse) 
2896   
2897          # Define dx.map settings. 
2898          ds.dx_inc = 4 
2899          ds.dx_params = ['dw', 'pA', 'kex'] 
2900   
2901          res_name, res_num, spin_name, params = cur_spins[0] 
2902          cur_spin_id = ":%i@%s"%(res_num, spin_name) 
2903          cur_spin = return_spin(cur_spin_id) 
2904   
2905          print("Params for dx map is") 
2906          print(ds.dx_params) 
2907          print("Point param for dx map is") 
2908          print(ds.dx_set_val) 
2909          cur_model = model_analyse.replace(' ', '_') 
2910          file_name_map = "%s_map%s" % (cur_model, cur_spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
2911          file_name_point = "%s_point%s" % (cur_model, cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_')) 
2912          self.interpreter.dx.map(params=ds.dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=ds.dx_inc, lower=None, upper=None, axis_incs=10, file_prefix=file_name_map, dir=ds.resdir, point=[ds.dx_set_val, ds.dx_clust_val], point_file=file_name_point, create_par_file=True) 
2913   
2914          ## Check for file creation 
2915          # Set filepaths. 
2916          map_cfg = ds.tmpdir+sep+file_name_map+".cfg" 
2917          map_net = ds.tmpdir+sep+file_name_map+".net" 
2918          map_general = ds.tmpdir+sep+file_name_map+".general" 
2919          map_par = get_file_path(file_name=file_name_map+".par", dir=ds.tmpdir) 
2920          map_plot = get_file_path(file_name=file_name_map+".py", dir=ds.tmpdir) 
2921   
2922          point_general = ds.tmpdir+sep+file_name_point+".general" 
2923          point_point = ds.tmpdir+sep+file_name_point 
2924          point_par = get_file_path(file_name=file_name_point+".par", dir=ds.tmpdir) 
2925   
2926          # Test the files exists. 
2927          self.assert_(access(map_cfg, F_OK)) 
2928          self.assert_(access(map_net, F_OK)) 
2929          self.assert_(access(map_general, F_OK)) 
2930          self.assert_(access(map_par, F_OK)) 
2931          self.assert_(access(map_plot, F_OK)) 
2932          self.assert_(access(point_general, F_OK)) 
2933          self.assert_(access(point_point, F_OK)) 
2934          self.assert_(access(point_par, F_OK)) 
2935   
2936          # Open the files for testing. 
2937          # Check the cfg file. 
2938          print("\nChecking the dx map .cfg file.") 
2939          res_file = [ 
2940              '//'+"\n", 
2941              '//'+"\n", 
2942              '// time: Thu May  8 18:55:31 2014'+"\n", 
2943              '//'+"\n", 
2944              '// version: 3.2.0 (format), 4.3.2 (DX)'+"\n", 
2945              '//'+"\n", 
2946              '//'+"\n", 
2947              '// panel[0]: position = (0.0164,0.0000), size = 0.2521x0.1933, startup = 1, devstyle = 1'+"\n", 
2948              '// title: value = Control Panel'+"\n", 
2949              '//'+"\n", 
2950              '// workspace: width = 251, height = 142'+"\n", 
2951              '// layout: snap = 0, width = 50, height = 50, align = NN'+"\n", 
2952              '//'+"\n", 
2953              '// interactor Selector[1]: num_components = 1, value = 1 '+"\n", 
2954              '// selections: maximum = 2, current = 0 '+"\n", 
2955              '// option[0]: name = "Colour", value = 1'+"\n", 
2956              '// option[1]: name = "Grey", value = 2'+"\n", 
2957              '// instance: panel = 0, x = 81, y = 6, style = Scrolled List, vertical = 1, size = 170x136'+"\n", 
2958              '// label: value = Colour Selector'+"\n", 
2959              '//'+"\n", 
2960              '// node Image[3]:'+"\n", 
2961              '// title: value = Surface'+"\n", 
2962              '// depth: value = 24'+"\n", 
2963              '// window: position = (0.0000,0.0400), size = 0.9929x0.9276'+"\n", 
2964          ] 
2965          file = open(map_cfg, 'r') 
2966          lines = file.readlines() 
2967          file.close() 
2968          for i in range(len(res_file)): 
2969              # Skip time point 
2970              if i == 2: 
2971                  continue 
2972              self.assertEqual(res_file[i], lines[i]) 
2973   
2974          print("\nChecking the dx map .general file.") 
2975          res_file = [ 
2976              'file = CR72_map_1_N'+"\n", 
2977              'grid = 5 x 5 x 5'+"\n", 
2978              'format = ascii'+"\n", 
2979              'interleaving = field'+"\n", 
2980              'majority = row'+"\n", 
2981              'field = data'+"\n", 
2982              'structure = scalar'+"\n", 
2983              'type = float'+"\n", 
2984              'dependency = positions'+"\n", 
2985              'positions = regular, regular, regular, 0, 1, 0, 1, 0, 1'+"\n", 
2986              ''+"\n", 
2987              'end'+"\n", 
2988          ] 
2989          file = open(map_general, 'r') 
2990          lines = file.readlines() 
2991          file.close() 
2992          for i in range(len(res_file)): 
2993              # Skip time point 
2994              #if i == 2: 
2995              #    continue 
2996              self.assertEqual(res_file[i], lines[i]) 
2997   
2998          print("\nChecking the dx point .general file.") 
2999          res_file = [ 
3000              'file = CR72_point_1_N'+"\n", 
3001              'points = 2'+"\n", 
3002              'format = ascii'+"\n", 
3003              'interleaving = field'+"\n", 
3004              'field = locations, field0'+"\n", 
3005              'structure = 3-vector, scalar'+"\n", 
3006              'type = float, float'+"\n", 
3007              ''+"\n", 
3008              'end'+"\n", 
3009          ] 
3010          file = open(point_general, 'r') 
3011          lines = file.readlines() 
3012          file.close() 
3013          for i in range(len(res_file)): 
3014              # Skip time point 
3015              #if i == 2: 
3016              #    continue 
3017              self.assertEqual(res_file[i], lines[i]) 
3018   
3019          print("\nChecking the dx point point file.") 
3020          res_file = [ 
3021              '0.8            3.92           0.39964        1'+"\n", 
3022              '0.76981        3.9169         0.41353        1'+"\n", 
3023          ] 
3024          file = open(point_point, 'r') 
3025          lines = file.readlines() 
3026          file.close() 
3027          for i in range(len(res_file)): 
3028              # Skip time point 
3029              #if i == 2: 
3030              #    continue 
3031              self.assertEqual(res_file[i], lines[i]) 
3032   
3033          print("\nChecking the dx point par file.") 
3034          res_file = [ 
3035              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
3036              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
3037              '1      1.92453    0.98961    1034.72206    6396.02770    1         1.92453    0.98961    1034.72206    6396.02770    '+"\n", 
3038          ] 
3039          res_file2 = [ 
3040              '# i    dw         pA         kex           chi2          i_sort    dw_sort    pA_sort    kex_sort      chi2_sort     '+"\n", 
3041              '0      2.00000    0.99000    1000.00000    6185.84926    0         2.00000    0.99000    1000.00000    6185.84926    '+"\n", 
3042              '1      1.92452    0.98961    1034.72424    6396.02439    1         1.92452    0.98961    1034.72424    6396.02439    '+"\n", 
3043          ]  # Python 2.5 and 3.1. 
3044          file = open(point_par, 'r') 
3045          lines = file.readlines() 
3046          file.close() 
3047          for i in range(len(res_file)): 
3048              if lines[i] != res_file[i] and lines[i] != res_file2[i]: 
3049                  self.assertEqual(res_file[i], lines[i]) 
3050   
3051          print("\nChecking the matplotlib surface plot file.") 
3052          res_file = [ 
3053              'from copy import deepcopy'+"\n", 
3054              'import numpy as np'+"\n", 
3055              'import scipy.interpolate'+"\n", 
3056              'from numpy.ma import masked_where'+"\n", 
3057              ''+"\n", 
3058              'from mpl_toolkits.mplot3d import axes3d'+"\n", 
3059              'import matplotlib.pyplot as plt'+"\n", 
3060              'from matplotlib import cm'+"\n", 
3061              ''+"\n", 
3062              '# Open file and get header.'+"\n", 
3063              'mapfile_name = "%s.par"'%file_name_map+"\n", 
3064              'pointfile_name = "%s.par"'%file_name_point+"\n", 
3065              ''+"\n", 
3066          ] 
3067          file = open(map_plot, 'r') 
3068          lines = file.readlines() 
3069          file.close() 
3070          for i in range(len(res_file)): 
3071              self.assertEqual(res_file[i], lines[i]) 
3072   
3073   
3074 -    def test_curve_type_cpmg_fixed_time(self): 
3075          """Test the curve type detection using the Dr. Flemming Hansen's CPMG fixed time test data.""" 
3076   
3077          # Reset. 
3078          self.interpreter.reset() 
3079   
3080          # Load the base data. 
3081          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen' 
3082          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3083   
3084          # The type. 
3085          curve_type = get_curve_type(id='500_133.33.in') 
3086          self.assertEqual(curve_type, 'fixed time') 
3087   
3088   
3089 -    def test_curve_type_r1rho_exponential(self, model=None): 
3090          """Test the curve type detection using the 'M61' exponential test data.""" 
3091   
3092          # Reset. 
3093          self.interpreter.reset() 
3094   
3095          # Load the base data. 
3096          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_on_res_m61' 
3097          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3098   
3099          # The type. 
3100          curve_type = get_curve_type(id='nu_2000_ncyc9') 
3101          self.assertEqual(curve_type, 'exponential') 
3102   
3103   
3104 -    def test_curve_type_r1rho_fixed_time(self, model=None): 
3105          """Test the curve type detection using the 'TP02' fixed time test data.""" 
3106   
3107          # Reset. 
3108          self.interpreter.reset() 
3109   
3110          # Load the base data. 
3111          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r1rho_off_res_tp02' 
3112          self.interpreter.state.load(data_path+sep+'r2eff_values') 
3113   
3114          # The type. 
3115          curve_type = get_curve_type(id='nu_1000.0_500MHz') 
3116          self.assertEqual(curve_type, 'fixed time') 
3117   
3118   
3119 -    def test_dpl94_data_to_dpl94(self): 
3120          """Test the relaxation dispersion 'DPL94' model curve fitting to fixed time synthetic data.""" 
3121   
3122          # Fixed time variable. 
3123          ds.fixed = True 
3124   
3125          # Execute the script. 
3126          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_dpl94.py') 
3127   
3128          # The original parameters. 
3129          i0 = [100000.0, 20000.0] 
3130          r1rho_prime = [2.25, 24.0] 
3131          pA = 0.7 
3132          kex = 1000.0 
3133          delta_omega = [1.0, 2.0] 
3134          phi_ex = [] 
3135          for i in range(2): 
3136              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
3137   
3138          # Switch to the 'DPL94' model data pipe, then check for each spin. 
3139          self.interpreter.pipe.switch('DPL94 - relax_disp') 
3140          spin_index = 0 
3141          for spin, spin_id in spin_loop(return_id=True): 
3142              # Printout. 
3143              print("\nSpin %s." % spin_id) 
3144   
3145              # Check the fitted parameters. 
3146              self.assertAlmostEqual(spin.r2['R1rho - 800.00000000 MHz']/10, r1rho_prime[spin_index]/10, 2) 
3147              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
3148              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
3149   
3150              # Increment the spin index. 
3151              spin_index += 1 
3152   
3153   
3154 -    def test_dx_map_clustered(self): 
3155          """Test making dx_map for residues under clustered calculation. 
3156   
3157          This uses CPMG data from: 
3158              - Webb H, Tynan-Connolly BM, Lee GM, Farrell D, O'Meara F, Soendergaard CR, Teilum K, Hewage C, McIntosh LP, Nielsen JE 
3159                Remeasuring HEWL pK(a) values by NMR spectroscopy: methods, analysis, accuracy, and implications for theoretical pK(a) calculations. 
3160                (2011), Proteins: Struct, Funct, Bioinf 79(3):685-702, U{DOI 10.1002/prot.22886<http://dx.doi.org/10.1002/prot.22886>} 
3161          """ 
3162   
3163          # Define path to data  
3164          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'HWebb_KTeilum_Proteins_Struct_Funct_Bioinf_2011' 
3165   
3166          # Read data. 
3167          self.interpreter.results.read(prev_data_path + sep + 'FT_-_CR72_-_min_-_128_-_free_spins') 
3168   
3169          # Get residue of interest. 
3170          cur_spin_id = ":%i@%s"%(52, 'N') 
3171          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3172   
3173          # Get the spin container. 
3174          cur_spin = return_spin(cur_spin_id) 
3175   
3176          # Get the chi2 value 
3177          pre_chi2 = cur_spin.chi2 
3178   
3179          # Then do a local minimisation. 
3180          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3181          self.interpreter.minimise.calculate() 
3182   
3183          # Get the chi2 value after calculation. 
3184          calc_chi2 = cur_spin.chi2 
3185   
3186          # Assert calculation is equal. 
3187          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3188   
3189          # Define dx.map settings. 
3190          dx_inc = 2 
3191          dx_inc_sides = dx_inc / 2 
3192   
3193          dx_params = ['dw', 'pA', 'kex'] 
3194          dx_point_clustered_min = [cur_spin.dw, cur_spin.pA, cur_spin.kex] 
3195   
3196          print("Params for dx map is") 
3197          print(dx_params) 
3198          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3199          print(dx_point_clustered_min) 
3200   
3201          # Define file_names. 
3202          cur_model = 'CR72' 
3203          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3204          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3205   
3206          # Step-size of parameter is 10 % 
3207          param_delta = 0.1 
3208   
3209          # Determine bounds for lower and upper 
3210          lower = [] 
3211          upper = [] 
3212          for i, param_val in enumerate(dx_point_clustered_min): 
3213              param = dx_params[i] 
3214              step_val = param_delta * param_val 
3215              step_length = step_val * dx_inc_sides 
3216   
3217              # Calculate value 
3218              low_val = param_val - step_length 
3219              lower.append(low_val) 
3220   
3221              upp_val = param_val + step_length 
3222              upper.append(upp_val) 
3223   
3224              print("For param %s, lower=%3.3f, upper=%3.3f, step_value=%3.3f, steps=%i, centered at=%3.3f"% (param, low_val, upp_val, step_val, dx_inc, param_val)) 
3225   
3226          # If the number of increments are 2, there will be 3 point calculations per parameter. 
3227          # Since we have ordered the lower and upper limits on sides of the parameter, the middle index should give us the expected global value. 
3228          dx_param_indexes = dx_inc + 1 
3229          dx_point_index = dx_inc_sides + 1 
3230   
3231          # Find the line number. 
3232          line = 1 
3233          for i in range(1, dx_param_indexes + 1): 
3234              for j in range(1, dx_param_indexes + 1): 
3235                  for k in range(1, dx_param_indexes + 1): 
3236                      if i == dx_point_index and j == dx_point_index and k == dx_point_index: 
3237                          line_chi2 = line 
3238                      # Add to line counter. 
3239                      line += 1 
3240   
3241          # Define temporary folder. 
3242          result_dir = self.tmpdir 
3243   
3244          # For testing. 
3245          #result_dir = None 
3246          #lower = None 
3247          #upper = None 
3248          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3249   
3250   
3251          # Then do the map. 
3252          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point) 
3253   
3254          # Print where to locate values. 
3255          nr_chi2_val = dx_param_indexes**3 
3256          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3257          print("Global chi2=%3.3f, Calc_chi=%3.3f, map_line_chi2=%i" % (pre_chi2, calc_chi2, line_chi2) ) 
3258   
3259          ## Check for file creation 
3260          # Set filepaths. 
3261          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3262          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3263          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3264          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3265   
3266          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3267          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3268   
3269          # Test the files exists. 
3270          self.assert_(access(map_cfg, F_OK)) 
3271          self.assert_(access(map_net, F_OK)) 
3272          self.assert_(access(map_general, F_OK)) 
3273          self.assert_(access(point_general, F_OK)) 
3274          self.assert_(access(point_point, F_OK)) 
3275   
3276          # Open the file, and assert the chi2 value is as expected. 
3277          get_data = extract_data(file=map_name) 
3278   
3279          # Extract line 0, column 0. 
3280          test = float(get_data[line_chi2-1][0]) 
3281   
3282          # Assert. 
3283          self.assertAlmostEqual(test, pre_chi2,  6) 
3284   
3285   
3286 -    def test_dx_map_clustered_create_par_file(self): 
3287          """Test making dx_map for residues under clustered calculation, and the creation of the parameter file. 
3288   
3289          U{Task #7860<https://gna.org/task/index.php?7860>} : When dx_map is issued, create a parameter file which maps parameters to chi2 value. 
3290   
3291          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
3292          """ 
3293   
3294          # Define path to data  
3295          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+'surface_chi2_clustered_fitting' 
3296   
3297          # Read data. 
3298          self.interpreter.results.read(prev_data_path + sep + 'coMDD_-_TSMFK01_-_min_-_32_-_free_spins.bz2') 
3299   
3300          # Get residue of interest. 
3301          cur_spin_id = ":%i@%s"%(65, 'N') 
3302          cur_spin_id_str = cur_spin_id .replace('#', '_').replace(':', '_').replace('@', '_') 
3303   
3304          # Get the spin container. 
3305          cur_spin = return_spin(cur_spin_id) 
3306   
3307          # Get the chi2 value 
3308          pre_chi2 = cur_spin.chi2 
3309   
3310          # Then do a local minimisation. 
3311          #self.interpreter.select.spin(":%i@%s"%(2, 'N')) 
3312          self.interpreter.minimise.calculate() 
3313   
3314          # Get the chi2 value after calculation. 
3315          calc_chi2 = cur_spin.chi2 
3316   
3317          # Assert calculation is equal. 
3318          self.assertAlmostEqual(pre_chi2, calc_chi2) 
3319   
3320          # Define dx.map settings. 
3321          dx_inc = 2 
3322          dx_params = ['dw', 'k_AB', 'r2a'] 
3323          dx_point_clustered_min = [cur_spin.dw, cur_spin.k_AB, cur_spin.r2a['SQ CPMG - 499.86214000 MHz']] 
3324   
3325          print("Params for dx map is") 
3326          print(dx_params) 
3327          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3328          print(dx_point_clustered_min) 
3329   
3330          # Define file_names. 
3331          cur_model = 'TSMFK01' 
3332          file_name_map = "%s_map%s" % (cur_model, cur_spin_id_str) 
3333          file_name_point = "%s_point%s" % (cur_model, cur_spin_id_str) 
3334   
3335          # Determine bounds for lower and upper 
3336          lower = [dx_point_clustered_min[0], dx_point_clustered_min[1], dx_point_clustered_min[2]] 
3337          upper = [19.0, 2.4, 9.5] 
3338   
3339          # Define temporary folder. 
3340          result_dir = self.tmpdir 
3341   
3342          # For testing. 
3343          #result_dir = None 
3344          #self.interpreter.relax_disp.cluster(cluster_id='free spins', spin_id=cur_spin_id) 
3345   
3346          # Then do the map. 
3347          self.interpreter.dx.map(params=dx_params, map_type='Iso3D', spin_id=cur_spin_id, inc=dx_inc, lower=lower, upper=upper, axis_incs=10, file_prefix=file_name_map, dir=result_dir, point=dx_point_clustered_min, point_file=file_name_point, create_par_file=True) 
3348   
3349          # Print where to locate values. 
3350          nr_chi2_val = (dx_inc + 1)**3 
3351          print("Nr of chi2 calculations are=%i"%nr_chi2_val) 
3352          print("Global chi2=%3.3f, Calc_chi=%3.3f" % (pre_chi2, calc_chi2) ) 
3353   
3354          ## Check for file creation 
3355          # Set filepaths. 
3356          map_name = get_file_path(file_name=file_name_map, dir=result_dir) 
3357          map_cfg = get_file_path(file_name=file_name_map+".cfg", dir=result_dir) 
3358          map_net = get_file_path(file_name=file_name_map+".net", dir=result_dir) 
3359          map_general = get_file_path(file_name=file_name_map+".general", dir=result_dir) 
3360          map_par = get_file_path(file_name=file_name_map+".par", dir=result_dir) 
3361   
3362          point_general = get_file_path(file_name=file_name_point+".general", dir=result_dir) 
3363          point_point = get_file_path(file_name=file_name_point, dir=result_dir) 
3364   
3365          # Test the files exists. 
3366          self.assert_(access(map_cfg, F_OK)) 
3367          self.assert_(access(map_net, F_OK)) 
3368          self.assert_(access(map_general, F_OK)) 
3369          self.assert_(access(map_par, F_OK)) 
3370          self.assert_(access(point_general, F_OK)) 
3371          self.assert_(access(point_point, F_OK)) 
3372   
3373          print("\nParams for dx map is") 
3374          print(dx_params) 
3375          print("Point param for dx map is, with chi2=%3.3f"%pre_chi2) 
3376          print(dx_point_clustered_min, "\n") 
3377   
3378          # Open the parameter chi2 file, and assert the chi2 value in the sorted parameter file is not lower that than the global minimisation. 
3379          get_data = extract_data(file=map_par) 
3380   
3381          # Extract line 1, column 9. 
3382          test = float(get_data[1][9]) 
3383   
3384          # Print data if map contain a lower value than the global minimised value. 
3385          if test < pre_chi2: 
3386              print("\nInitial clustered minimised chi2 value is=%3.3f, whereby the minimum map value is=%3.3f\n" % (pre_chi2, test)) 
3387              for line in get_data: 
3388                  print(line) 
3389   
3390          # Assert that the initial global chi2 is lower than the map value. 
3391   
3392          # The following test was taken out, since this a particular interesting case. 
3393          # There exist a double minimum, where relax has not found the global minimum. 
3394          # This is due to not grid searching for R2A, but using the minimum  
3395          #self.assert_(pre_chi2 < test) 
3396   
3397   
3398 -    def test_estimate_r2eff_err(self): 
3399          """Test the user function for estimating R2eff errors from exponential curve fitting. 
3400   
3401          This follows Task 7822. 
3402          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3403   
3404          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3405          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3406          """ 
3407   
3408          # Cluster residues 
3409          cluster_ids = [ 
3410          ":13@N", 
3411          ":15@N", 
3412          ":16@N", 
3413          ":25@N", 
3414          ":26@N", 
3415          ":28@N", 
3416          ":39@N", 
3417          ":40@N", 
3418          ":41@N", 
3419          ":43@N", 
3420          ":44@N", 
3421          ":45@N", 
3422          ":49@N", 
3423          ":52@N", 
3424          ":53@N"] 
3425   
3426          # Load the data. 
3427          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3428   
3429          # The dispersion models. 
3430          MODELS = [MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3431   
3432          # The grid search size (the number of increments per dimension). 
3433          GRID_INC = None 
3434   
3435          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3436          MC_NUM = 3 
3437   
3438          # Model selection technique. 
3439          MODSEL = 'AIC' 
3440   
3441          # Execute the auto-analysis (fast). 
3442          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3443          OPT_FUNC_TOL = 1e-25 
3444          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3445          OPT_MAX_ITERATIONS = 10000000 
3446          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3447   
3448          result_dir_name = ds.tmpdir 
3449   
3450          # Make all spins free 
3451          for curspin in cluster_ids: 
3452              self.interpreter.relax_disp.cluster('free spins', curspin) 
3453              # Shut them down 
3454              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
3455   
3456          # Select only a subset of spins for global fitting 
3457          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3458          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3459   
3460          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3461          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3462   
3463          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3464          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3465   
3466          # Set the model. 
3467          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3468   
3469          # Check if intensity errors have already been calculated. 
3470          check_intensity_errors() 
3471   
3472          # Do a grid search. 
3473          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
3474   
3475          # Minimise. 
3476          self.interpreter.minimise.execute(min_algor='Newton', constraints=False, verbosity=1) 
3477   
3478          # Estimate R2eff errors. 
3479          self.interpreter.relax_disp.r2eff_err_estimate() 
3480   
3481          r1_fit = True 
3482   
3483          # Run the analysis. 
3484          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3485   
3486          # Verify the data. 
3487          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3488   
3489   
3490 -    def test_estimate_r2eff_err_auto(self): 
3491          """Test the user function for estimating R2eff errors from exponential curve fitting, via the auto_analyses menu. 
3492   
3493          This follows Task 7822. 
3494          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3495   
3496          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3497          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3498          """ 
3499   
3500          # Cluster residues 
3501          cluster_ids = [ 
3502          ":13@N", 
3503          ":15@N", 
3504          ":16@N", 
3505          ":25@N", 
3506          ":26@N", 
3507          ":28@N", 
3508          ":39@N", 
3509          ":40@N", 
3510          ":41@N", 
3511          ":43@N", 
3512          ":44@N", 
3513          ":45@N", 
3514          ":49@N", 
3515          ":52@N", 
3516          ":53@N"] 
3517   
3518          # Load the data. 
3519          #self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
3520          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
3521   
3522          # Set pipe name, bundle and type. 
3523          pipe_name = 'base pipe' 
3524          pipe_bundle = 'relax_disp' 
3525          pipe_type = 'relax_disp' 
3526   
3527          # Create the data pipe. 
3528          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
3529   
3530          file = data_path + '1_setup_r1rho_GUI.py' 
3531          self.interpreter.script(file=file, dir=None) 
3532   
3533          # The dispersion models. 
3534          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
3535   
3536          # The grid search size (the number of increments per dimension). 
3537          GRID_INC = None 
3538   
3539          # The number of Monte Carlo simulations to be used for error analysis for exponential curve fitting of R2eff. 
3540          # When set to minus 1, estimation of the errors will be extracted from the covariance matrix. 
3541          # This is HIGHLY likely to be wrong, but can be used in an initial test fase. 
3542          EXP_MC_NUM = -1 
3543   
3544          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
3545          MC_NUM = 3 
3546   
3547          # Model selection technique. 
3548          MODSEL = 'AIC' 
3549   
3550          # Execute the auto-analysis (fast). 
3551          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
3552          OPT_FUNC_TOL = 1e-25 
3553          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
3554          OPT_MAX_ITERATIONS = 10000000 
3555          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
3556   
3557          # Make all spins free 
3558          #for curspin in cluster_ids: 
3559          #    self.interpreter.relax_disp.cluster('free spins', curspin) 
3560          #    # Shut them down 
3561          #    self.interpreter.deselect.spin(spin_id=curspin, boolean='OR', change_all=False) 
3562   
3563          # Make all spins free 
3564          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
3565   
3566          # Select only a subset of spins for global fitting 
3567          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
3568          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
3569   
3570          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
3571          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
3572   
3573          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
3574          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
3575   
3576          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3577              print(spin_id) 
3578   
3579          result_dir_name = self.tmpdir 
3580          r1_fit = True 
3581   
3582          # Run the analysis. 
3583          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=EXP_MC_NUM, modsel=MODSEL, r1_fit=r1_fit) 
3584   
3585          # Verify the data. 
3586          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='direct') 
3587   
3588   
3589 -    def test_estimate_r2eff_err_methods(self): 
3590          """Test the user function for estimating R2eff and associated errors for exponential curve fitting with different methods. 
3591          This is compared with a run where erros are estimated by 2000 Monte Carlo simulations. 
3592   
3593          This follows Task 7822. 
3594          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
3595   
3596          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
3597          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
3598   
3599          NOTE: The difference in the methods was due to a bug in relax! 
3600          U{bug #22554<https://gna.org/bugs/index.php?22554>}. The distribution of intensity with errors in Monte-Carlo simulations are markedly more narrow than expected. 
3601   
3602          This dataset is old, and includes 2000 Monte-Carlo simulations, which is performed wrong. 
3603          """ 
3604   
3605          # Define data path. 
3606          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000"  +sep+ "R2eff" 
3607   
3608          # Create pipe. 
3609          self.interpreter.pipe.create('MC_2000', 'relax_disp') 
3610   
3611          # Read results for 2000 MC simulations. 
3612          self.interpreter.results.read(prev_data_path + sep + 'results') 
3613   
3614          # Start dic. 
3615          my_dic = {} 
3616          param_key_list = [] 
3617   
3618          # Do boot strapping ? 
3619          do_boot = True 
3620          if do_boot: 
3621              min_algor = 'Newton' 
3622              min_options = () 
3623              sim_boot = 200 
3624              scaling_list = [1.0, 1.0] 
3625   
3626          # First check sim values. 
3627          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3628              # Add key to dic. 
3629              my_dic[spin_id] = {} 
3630   
3631              # Loop over sim. 
3632              for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3633                  # Loop over all exp type. 
3634                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3635                      # Generate the param_key. 
3636                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3637                      r2eff_sim_point = r2eff_sim[param_key] 
3638                      i0_sim_point = cur_spin.r2eff_sim[i][param_key] 
3639   
3640                      # Assert point are higher than 0.0. 
3641                      #point_info = "r2eff=%3.2f i0=%3.2f, at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f, at sim index %i." % (r2eff_sim_point, i0_sim_point, frq/1E6, offset, point, i) 
3642                      #print(point_info) 
3643                      self.assert_(r2eff_sim_point > 0.0) 
3644                      self.assert_(i0_sim_point > 0.0) 
3645   
3646          # Get the data. 
3647          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3648              # Generate spin string. 
3649              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3650   
3651              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3652                  # Generate the param_key. 
3653                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3654   
3655                  # Loop over all sim, and collect data. 
3656                  r2eff_sim_l = [] 
3657                  i0_sim_l = [] 
3658                  for i, r2eff_sim in enumerate(cur_spin.r2eff_sim): 
3659                      i0_sim = cur_spin.i0_sim[i] 
3660   
3661                      r2eff_sim_i = r2eff_sim[param_key] 
3662                      r2eff_sim_l.append(r2eff_sim_i) 
3663                      i0_sim_i = i0_sim[param_key] 
3664                      i0_sim_l.append(i0_sim_i) 
3665   
3666                  # Take the standard deviation of all values. 
3667                  r2eff_sim_err = std(asarray(r2eff_sim_l), ddof=1) 
3668                  i0_sim_err = std(asarray(i0_sim_l), ddof=1) 
3669   
3670                  # Append key. 
3671                  param_key_list.append(param_key) 
3672   
3673                  # Add key to dic. 
3674                  my_dic[spin_id][param_key] = {} 
3675   
3676                  # Get the value. 
3677                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
3678                  r2eff_err = getattr(cur_spin, 'r2eff_err')[param_key] 
3679                  i0 = getattr(cur_spin, 'i0')[param_key] 
3680                  i0_err = getattr(cur_spin, 'i0_err')[param_key] 
3681   
3682                  # Save to dic. 
3683                  my_dic[spin_id][param_key]['r2eff'] = r2eff 
3684                  my_dic[spin_id][param_key]['r2eff_err'] = r2eff_err 
3685                  my_dic[spin_id][param_key]['i0'] = i0 
3686                  my_dic[spin_id][param_key]['i0_err'] = i0_err 
3687                  my_dic[spin_id][param_key]['r2eff_err_sim'] = r2eff_sim_err 
3688                  my_dic[spin_id][param_key]['i0_err_sim'] = i0_sim_err 
3689   
3690                  # Assert values are equal 
3691                  self.assertAlmostEqual(r2eff_sim_err, r2eff_err) 
3692                  self.assertAlmostEqual(i0_sim_err, i0_err) 
3693   
3694                  if do_boot: 
3695                      values = [] 
3696                      errors = [] 
3697                      times = [] 
3698                      for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
3699                          values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
3700                          errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
3701                          times.append(time) 
3702   
3703                      # Convert to numpy array. 
3704                      values = asarray(values) 
3705                      errors = asarray(errors) 
3706                      times = asarray(times) 
3707   
3708                      R_m_sim_l = [] 
3709                      I0_m_sim_l = [] 
3710                      for j in range(sim_boot): 
3711                          if j in range(0, 100000, 100): 
3712                              print("Simulation %i"%j) 
3713                          # Start minimisation. 
3714   
3715                          # Produce errors 
3716                          I_err = [] 
3717                          for j, error in enumerate(errors): 
3718                              I_error = gauss(values[j], error) 
3719                              I_err.append(I_error) 
3720                          # Convert to numpy array. 
3721                          I_err = asarray(I_err) 
3722   
3723                          x0 = [r2eff, i0] 
3724                          model = Relax_fit_opt(model='exp', num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3725   
3726                          params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, full_output=True, print_flag=0) 
3727                          R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
3728                          R_m_sim_l.append(R_m_sim_j) 
3729                          I0_m_sim_l.append(I0_m_sim_j) 
3730   
3731                      # Get stats on distribution. 
3732                      sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
3733                      sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
3734                      my_dic[spin_id][param_key]['r2eff_err_boot'] = sigma_R_sim 
3735                      my_dic[spin_id][param_key]['i0_err_boot'] = sigma_I0_sim 
3736   
3737   
3738          # A new data pipe. 
3739          self.interpreter.pipe.copy(pipe_from='MC_2000', pipe_to='r2eff_est') 
3740          self.interpreter.pipe.switch(pipe_name='r2eff_est') 
3741   
3742          # Delete old errors. 
3743          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3744              delattr(cur_spin, 'r2eff_err') 
3745              delattr(cur_spin, 'i0_err') 
3746   
3747          # Set the model. 
3748          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
3749   
3750          # Estimate R2eff and errors. 
3751          self.interpreter.relax_disp.r2eff_err_estimate(verbosity=0) 
3752   
3753          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
3754              # Generate spin string. 
3755              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
3756   
3757              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
3758                  # Generate the param_key. 
3759                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
3760   
3761                  # Get the value. 
3762                  r2eff_est = getattr(cur_spin, 'r2eff')[param_key] 
3763                  r2eff_err_est = getattr(cur_spin, 'r2eff_err')[param_key] 
3764                  i0_est = getattr(cur_spin, 'i0')[param_key] 
3765                  i0_err_est = getattr(cur_spin, 'i0_err')[param_key] 
3766   
3767                  # Get from dic. 
3768                  r2eff = my_dic[spin_id][param_key]['r2eff'] 
3769                  r2eff_err = my_dic[spin_id][param_key]['r2eff_err'] 
3770                  i0 = my_dic[spin_id][param_key]['i0'] 
3771                  i0_err = my_dic[spin_id][param_key]['i0_err'] 
3772                  r2eff_sim_err = my_dic[spin_id][param_key]['r2eff_err_sim'] 
3773                  i0_sim_err = my_dic[spin_id][param_key]['i0_err_sim'] 
3774   
3775                  if do_boot: 
3776                      r2eff_boot_err = my_dic[spin_id][param_key]['r2eff_err_boot'] 
3777                      i0_boot_err = my_dic[spin_id][param_key]['i0_err_boot'] 
3778                  else: 
3779                      r2eff_boot_err = 0.0 
3780                      i0_boot_err = 0.0 
3781   
3782                  print("%s at %3.1f MHz, for offset=%3.3f ppm and dispersion point %-5.1f." % (exp_type, frq/1E6, offset, point) ) 
3783                  print("r2eff=%3.3f/%3.3f r2eff_err=%3.4f/%3.4f/%3.4f/%3.4f" % (r2eff, r2eff_est, r2eff_err, r2eff_err_est, r2eff_sim_err, r2eff_boot_err) ), 
3784                  print("i0=%3.3f/%3.3f i0_err=%3.4f/%3.4f/%3.4f/%3.4f\n" % (i0, i0_est, i0_err, i0_err_est, i0_sim_err, i0_boot_err) ) 
3785   
3786   
3787          # Now do it manually. 
3788          estimate_r2eff(method='scipy.optimize.leastsq') 
3789   
3790          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=False) 
3791          estimate_r2eff(method='minfx', min_algor='simplex', c_code=True, constraints=False, chi2_jacobian=True) 
3792   
3793          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=False) 
3794          estimate_r2eff(method='minfx', min_algor='simplex', c_code=False, constraints=False, chi2_jacobian=True) 
3795   
3796          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=False) 
3797          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=True, constraints=False, chi2_jacobian=True) 
3798   
3799          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=False) 
3800          estimate_r2eff(method='minfx', min_algor='BFGS', c_code=False, constraints=False, chi2_jacobian=True) 
3801   
3802          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=False) 
3803          estimate_r2eff(method='minfx', min_algor='Newton', c_code=True, constraints=False, chi2_jacobian=True) 
3804   
3805   
3806   
3807 -    def test_exp_fit(self): 
3808          """Test the relaxation dispersion 'exp_fit' model curve fitting.""" 
3809   
3810          # Execute the script. 
3811          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'exp_fit.py') 
3812   
3813          # The original exponential curve parameters. 
3814          res_data = [ 
3815              [15., 10., 20000., 25000.], 
3816              [12., 11., 50000., 51000.], 
3817              [17., 9., 100000., 96000.] 
3818          ] 
3819   
3820          # List of parameters which do not belong to the model. 
3821          blacklist = ['cpmg_frqs', 'r2', 'rex', 'kex', 'r2a', 'k_AB', 'dw'] 
3822   
3823          # Checks for each residue. 
3824          for i in range(len(res_data)): 
3825              # Printout. 
3826              print("\nResidue number %s." % (i+1)) 
3827   
3828              # Check the fitted parameters. 
3829              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_1000.000'], res_data[i][0], places=2) 
3830              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].r2eff['r1rho_1200.00000000_0.000_2000.000'], res_data[i][1], places=2) 
3831              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_1000.000']/10000, res_data[i][2]/10000, places=3) 
3832              self.assertAlmostEqual(cdp.mol[0].res[i].spin[0].i0['r1rho_1200.00000000_0.000_2000.000']/10000, res_data[i][3]/10000, places=3) 
3833   
3834              # Check the simulation errors. 
3835              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_1000.000'] < 5.0) 
3836              self.assert_(cdp.mol[0].res[i].spin[0].r2eff_err['r1rho_1200.00000000_0.000_2000.000'] < 5.0) 
3837              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_1000.000']/10000 < 5.0) 
3838              self.assert_(cdp.mol[0].res[i].spin[0].i0_err['r1rho_1200.00000000_0.000_2000.000']/10000 < 5.0) 
3839   
3840              # Check that certain parameters are not present. 
3841              for param in blacklist: 
3842                  print("\tChecking for the absence of the '%s' parameter." % param) 
3843                  self.assert_(not hasattr(cdp.mol[0].res[i].spin[0], param)) 
3844   
3845          # Check the clustering information. 
3846          self.assert_(hasattr(cdp, 'clustering')) 
3847          keys = ['free spins', 'cluster'] 
3848          for key in keys: 
3849              self.assert_(key in cdp.clustering) 
3850          self.assert_('test' not in cdp.clustering) 
3851          self.assertEqual(cdp.clustering['free spins'], [':2@N']) 
3852          self.assertEqual(cdp.clustering['cluster'], [':1@N', ':3@N']) 
3853   
3854   
3855 -    def test_finite_value(self): 
3856          """Test return from C code, when parameters are wrong.  This can happen, if minfx takes a wrong step.""" 
3857   
3858          times = array([ 0.7,  1.,  0.8,  0.4,  0.9]) 
3859          I = array([ 476.76174875,  372.43328777,  454.20339981,  656.87936253,  419.16726341]) 
3860          errors = array([  9.48032653,  11.34093541,   9.35149017,  10.84867928,  12.17590736]) 
3861   
3862          scaling_list = [1.0, 1.0] 
3863          model = Relax_fit_opt(model='exp', num_params=2, values=I, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
3864   
3865          R = - 500. 
3866          I0 = 1000. 
3867          params = [R, I0] 
3868   
3869          chi2 = model.func(params) 
3870   
3871          print("The chi2 value returned from C-code for R=%3.2f and I0=%3.2f, then chi2=%3.2f"%(R, I0, chi2)) 
3872          self.assertNotEqual(chi2, inf) 
3873   
3874   
3875 -    def test_hansen_catia_input(self): 
3876          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CATIA. 
3877   
3878          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3879          """ 
3880   
3881          # Load the R2eff results file. 
3882          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
3883          self.interpreter.results.read(file_name) 
3884          self.interpreter.deselect.spin(':4') 
3885   
3886          # The spin isotopes. 
3887          self.interpreter.spin.isotope("15N") 
3888   
3889          # Generate the input files. 
3890          self.interpreter.relax_disp.catia_input(dir=ds.tmpdir, force=True) 
3891   
3892          # Check the r2eff set files. 
3893          print("\nChecking the R2eff input set files.") 
3894          files = ['data_set_500.inp', 'data_set_500.inp'] 
3895          for file in files: 
3896              self.assert_(access(ds.tmpdir+sep+file, F_OK)) 
3897          data_set_500 = [ 
3898              "ID=500\n", 
3899              "Sfrq = 500\n", 
3900              "Temperature = 0.0\n", 
3901              "Nucleus = N15\n", 
3902              "Couplednucleus = H1\n", 
3903              "Time_equil = 0.0\n", 
3904              "Pwx_cp = 0.0\n", 
3905              "Taub = 0.0\n", 
3906              "Time_T2 = 0.03\n", 
3907              "Xcar = 0.0\n", 
3908              "Seqfil = CW_CPMG\n", 
3909              "Minerror = (2.%;0.5/s)\n", 
3910              "Basis = (Iph_7)\n", 
3911              "Format = (0;1;2)\n", 
3912              "DataDirectory = /tmp/tmpNjOGNG/input_r2eff\n", 
3913              "Data = (\n", 
3914              " [70N;spin_70_N_500.cpmg];\n", 
3915              " [71N;spin_71_N_500.cpmg];\n", 
3916              ")\n", 
3917          ] 
3918          file = open(ds.tmpdir+sep+files[0]) 
3919          lines = file.readlines() 
3920          file.close() 
3921          for i in range(len(data_set_500)): 
3922              # Skip the data directory, as this is a random file name. 
3923              if i == 14: 
3924                  continue 
3925   
3926              self.assertEqual(data_set_500[i], lines[i]) 
3927   
3928          # Check the r2eff files. 
3929          print("\nChecking the R2eff input files.") 
3930          files = ['spin_70_N_500.cpmg', 'spin_70_N_800.cpmg', 'spin_71_N_500.cpmg', 'spin_71_N_800.cpmg'] 
3931          for file in files: 
3932              self.assert_(access(ds.tmpdir+sep+'input_r2eff'+sep+file, F_OK)) 
3933          spin_70_N_500 = [ 
3934              "#        nu_cpmg(Hz)              R2(1/s)              Esd(R2)\n", 
3935              "  66.666600000000003   16.045540885533605    0.310924686180635\n", 
3936              " 133.333300000000008   14.877924861181727    0.303217270671013\n", 
3937              " 200.000000000000000   14.357820247260586    0.299894424543361\n", 
3938              " 266.666600000000017   12.664494620416516    0.289532060485796\n", 
3939              " 333.333300000000008   12.363204802467891    0.287759631749322\n", 
3940              " 400.000000000000000   11.092532381134513    0.280514035409862\n", 
3941              " 466.666600000000017   10.566090057649893    0.277618625949722\n", 
3942              " 533.333300000000008    9.805806894657803    0.273544382200754\n", 
3943              " 600.000000000000000    9.564300692201730    0.272276309984954\n", 
3944              " 666.666600000000017    9.015633750407980    0.269441511838159\n", 
3945              " 733.333300000000008    8.607764958055581    0.267375134391053\n", 
3946              " 800.000000000000000    8.279997179221338    0.265739551961997\n", 
3947              " 866.666600000000017    8.474535940963516    0.266707642726566\n", 
3948              " 933.333300000000008    8.158972897365194    0.265141210539941\n", 
3949              "1000.000000000000000    7.988630509501972    0.264304105548559\n", 
3950          ] 
3951          file = open(ds.tmpdir+sep+'input_r2eff'+sep+files[0]) 
3952          lines = file.readlines() 
3953          file.close() 
3954          for i in range(len(lines)): 
3955              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
3956          for i in range(len(spin_70_N_500)): 
3957              self.assertEqual(spin_70_N_500[i], lines[i]) 
3958   
3959          # Check the main file. 
3960          print("\nChecking the main CATIA execution file.") 
3961          main_file = [ 
3962              "ReadDataset(data_set_500.inp)\n", 
3963              "ReadDataset(data_set_800.inp)\n", 
3964              "ReadParam_Global(ParamGlobal.inp)\n", 
3965              "ReadParam_Local(ParamSet1.inp)\n", 
3966              "\n", 
3967              "FreeLocalParam(all;Omega;false)\n", 
3968              "FreeLocalParam(all;R1iph_500;false)\n", 
3969              "FreeLocalParam(all;R1iph_800;false)\n", 
3970              "\n", 
3971              "Minimize(print=y;tol=1e-25;maxiter=10000000)\n", 
3972              "\n", 
3973              "PrintParam(output/GlobalParam.fit;global)\n", 
3974              "PrintParam(output/DeltaOmega.fit;DeltaO)\n", 
3975              "PrintData(output/)\n", 
3976              "\n", 
3977              "ChiSq(all;all)\n", 
3978              "exit(0)\n" 
3979          ] 
3980          file = open("%s%sFit.catia" % (ds.tmpdir, sep)) 
3981          lines = file.readlines() 
3982          file.close() 
3983          for i in range(len(main_file)): 
3984              self.assertEqual(main_file[i], lines[i]) 
3985   
3986   
3987 -    def test_hansen_cpmg_data_auto_analysis(self): 
3988          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
3989   
3990          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
3991          """ 
3992   
3993          # Set the model. 
3994          ds.models = [ 
3995              MODEL_NOREX, 
3996              MODEL_LM63, 
3997              MODEL_CR72, 
3998              MODEL_IT99 
3999          ] 
4000   
4001          # Execute the script. 
4002          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
4003          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
4004   
4005          # The R20 keys. 
4006          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4007          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4008   
4009          # The 'No Rex' model checks. 
4010          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4011          spin70 = return_spin(":70") 
4012          spin71 = return_spin(":71") 
4013          print("\n\nOptimised parameters:\n") 
4014          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4015          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4016          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4017          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4018          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4019          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4020          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4021          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4022          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4023          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4024   
4025          # The 'LM63' model checks. 
4026          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4027          spin70 = return_spin(":70") 
4028          spin71 = return_spin(":71") 
4029          print("\n\nOptimised parameters:\n") 
4030          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4031          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4032          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4033          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4034          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4035          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4036          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4037          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4038          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4039          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4040          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4041          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4042          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4043          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4044          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4045          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4046   
4047          # The 'CR72' model checks. 
4048          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4049          spin70 = return_spin(":70") 
4050          spin71 = return_spin(":71") 
4051          print("\n\nOptimised parameters:\n") 
4052          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4053          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4054          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4055          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4056          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4057          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4058          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4059          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4060          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4061          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4062          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4063          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4064          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4065          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4066          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4067          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4068          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4069          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4070          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4071   
4072   
4073 -    def test_hansen_cpmg_data_auto_analysis_numeric(self): 
4074          """Test of the numeric model only dispersion auto-analysis using Dr. Flemming Hansen's CPMG data. 
4075   
4076          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4077          """ 
4078   
4079          # Set the model and numeric flag. 
4080          ds.models = [ 
4081              MODEL_NOREX, 
4082              MODEL_CR72, 
4083              MODEL_NS_CPMG_2SITE_EXPANDED 
4084          ] 
4085          ds.numeric_only = True 
4086   
4087          # Execute the script. 
4088          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data.py') 
4089   
4090          # The R20 keys. 
4091          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4092          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4093   
4094          # The 'No Rex' model checks. 
4095          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4096          spin70 = return_spin(":70") 
4097          spin71 = return_spin(":71") 
4098          print("\n\nOptimised parameters:\n") 
4099          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4100          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4101          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4102          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4103          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4104          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4105          self.assertAlmostEqual(spin70.chi2/10000, 8973.84810025761/10000, 3) 
4106          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4107          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4108          self.assertAlmostEqual(spin71.chi2/10000, 3908.00127830003/10000, 3) 
4109   
4110          # The 'CR72' model checks. 
4111          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4112          spin70 = return_spin(":70") 
4113          spin71 = return_spin(":71") 
4114          print("\n\nOptimised parameters:\n") 
4115          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4116          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4117          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4118          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4119          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4120          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4121          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4122          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4123          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4124          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4125          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4126          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4127          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4128          self.assertAlmostEqual(spin71.r2[r20_key1], 5.003171547206, 3) 
4129          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797727492, 3) 
4130          self.assertAlmostEqual(spin71.pA, 0.985922406455826, 3) 
4131          self.assertAlmostEqual(spin71.dw, 2.00500965892672, 2) 
4132          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579617/10000, 3) 
4133          self.assertAlmostEqual(spin71.chi2, 15.6595374286822, 3) 
4134   
4135          # The 'NS CPMG 2-site expanded' model checks. 
4136          self.interpreter.pipe.switch(pipe_name='NS CPMG 2-site expanded - relax_disp') 
4137          spin70 = return_spin(":70") 
4138          spin71 = return_spin(":71") 
4139          print("\n\nOptimised parameters:\n") 
4140          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4141          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4142          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4143          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4144          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4145          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4146          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4147          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95815351460902, 3) 
4148          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39649535771294, 3) 
4149          self.assertAlmostEqual(spin70.pA, 0.989701014493195, 3) 
4150          self.assertAlmostEqual(spin70.dw, 5.67314464776128, 3) 
4151          self.assertAlmostEqual(spin70.kex/10000, 1713.65380495429/10000, 3) 
4152          self.assertAlmostEqual(spin70.chi2, 52.5106880917473, 3) 
4153          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99889337382435, 3) 
4154          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89822887466673, 3) 
4155          self.assertAlmostEqual(spin71.pA, 0.986709050819695, 3) 
4156          self.assertAlmostEqual(spin71.dw, 2.09238266766502, 2) 
4157          self.assertAlmostEqual(spin71.kex/10000, 2438.27019901422/10000, 3) 
4158          self.assertAlmostEqual(spin71.chi2, 15.1644906963987, 3) 
4159   
4160          # The final data pipe checks. 
4161          self.interpreter.pipe.switch(pipe_name='final - relax_disp') 
4162          spin70 = return_spin(":70") 
4163          spin71 = return_spin(":71") 
4164          self.assertEqual(spin70.model, 'NS CPMG 2-site expanded') 
4165          self.assertEqual(spin71.model, 'NS CPMG 2-site expanded') 
4166   
4167   
4168 -    def test_hansen_cpmg_data_auto_analysis_r2eff(self): 
4169          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data (using the R2eff data directly instead of peak intensities). 
4170   
4171          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4172          """ 
4173   
4174          # Set the model. 
4175          ds.models = [ 
4176              MODEL_NOREX, 
4177              MODEL_LM63, 
4178              MODEL_CR72, 
4179              MODEL_IT99 
4180          ] 
4181   
4182          # Execute the script. 
4183          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_r2eff_data.py') 
4184          self.interpreter.state.save('analysis_r2eff', dir=ds.tmpdir, force=True) 
4185   
4186          # The R20 keys. 
4187          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4188          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4189   
4190          # The 'No Rex' model checks. 
4191          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4192          spin70 = return_spin(":70") 
4193          spin71 = return_spin(":71") 
4194          print("\n\nOptimised parameters:\n") 
4195          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4196          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4197          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4198          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4199          self.assertAlmostEqual(spin70.r2[r20_key1], 10.5340593984683, 3) 
4200          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112170102734, 3) 
4201          self.assertAlmostEqual(spin70.chi2, 8973.84810025761, 3) 
4202          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83139953954648, 3) 
4203          self.assertAlmostEqual(spin71.r2[r20_key2], 8.90856319376098, 3) 
4204          self.assertAlmostEqual(spin71.chi2, 3908.00127830003, 3) 
4205   
4206          # The 'LM63' model checks. 
4207          self.interpreter.pipe.switch(pipe_name='LM63 - relax_disp') 
4208          spin70 = return_spin(":70") 
4209          spin71 = return_spin(":71") 
4210          print("\n\nOptimised parameters:\n") 
4211          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4212          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4213          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4214          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4215          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4216          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4217          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74326615264889, 2) 
4218          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57331164382438, 2) 
4219          self.assertAlmostEqual(spin70.phi_ex, 0.312767653822936, 3) 
4220          self.assertAlmostEqual(spin70.kex/10000, 4723.44390412119/10000, 3) 
4221          self.assertAlmostEqual(spin70.chi2, 363.534049046805, 3) 
4222          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00778024769786, 3) 
4223          self.assertAlmostEqual(spin71.r2[r20_key2], 6.83343630016037, 3) 
4224          self.assertAlmostEqual(spin71.phi_ex, 0.0553791362097596, 3) 
4225          self.assertAlmostEqual(spin71.kex/10000, 2781.67925957068/10000, 3) 
4226          self.assertAlmostEqual(spin71.chi2, 17.0776426190574, 3) 
4227   
4228          # The 'CR72' model checks. 
4229          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4230          spin70 = return_spin(":70") 
4231          spin71 = return_spin(":71") 
4232          print("\n\nOptimised parameters:\n") 
4233          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4234          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4235          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4236          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4237          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4238          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4239          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4240          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97233943292193, 3) 
4241          self.assertAlmostEqual(spin70.r2[r20_key2], 9.409506394526, 2) 
4242          self.assertAlmostEqual(spin70.pA, 0.989856804525044, 3) 
4243          self.assertAlmostEqual(spin70.dw, 5.60889078920945, 3) 
4244          self.assertAlmostEqual(spin70.kex/10000, 1753.01607073019/10000, 3) 
4245          self.assertAlmostEqual(spin70.chi2, 53.8382158551706, 3) 
4246          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00317154730225, 3) 
4247          self.assertAlmostEqual(spin71.r2[r20_key2], 6.90210797713541, 3) 
4248          self.assertAlmostEqual(spin71.pA, 0.985922406429147, 3) 
4249          self.assertAlmostEqual(spin71.dw, 2.00500965887772, 2) 
4250          self.assertAlmostEqual(spin71.kex/10000, 2481.10839579804/10000, 3) 
4251          self.assertAlmostEqual(spin71.chi2, 15.6595374288635, 3) 
4252   
4253   
4254 -    def test_hansen_cpmg_data_missing_auto_analysis(self): 
4255          """Test of the dispersion auto-analysis using Dr. Flemming Hansen's CPMG data with parts missing. 
4256   
4257          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4258          """ 
4259   
4260          # Set the model. 
4261          ds.models = [ 
4262              MODEL_R2EFF, 
4263              MODEL_NOREX, 
4264              MODEL_CR72, 
4265              MODEL_NS_CPMG_2SITE_EXPANDED 
4266          ] 
4267   
4268          # Execute the script. 
4269          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'hansen_data_missing.py') 
4270          self.interpreter.state.save('analysis_heights', dir=ds.tmpdir, force=True) 
4271   
4272          # The R20 keys. 
4273          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4274          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4275   
4276          # The 'No Rex' model checks. 
4277          self.interpreter.pipe.switch(pipe_name='No Rex - relax_disp') 
4278          spin4 = return_spin(":4") 
4279          spin70 = return_spin(":70") 
4280          spin71 = return_spin(":71") 
4281          print("\n\nOptimised parameters:\n") 
4282          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4283          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4284          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4285          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4286          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463084515171, 3) 
4287          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63220784651911, 3) 
4288          self.assertAlmostEqual(spin4.chi2, 26.7356700694891, 3) 
4289          self.assertAlmostEqual(spin70.r2[r20_key1], 10.534285641325, 3) 
4290          self.assertAlmostEqual(spin70.r2[r20_key2], 16.1112794857068, 3) 
4291          self.assertAlmostEqual(spin70.chi2, 8973.84809774722, 3) 
4292          self.assertAlmostEqual(spin71.r2[r20_key1], 5.83136858890037, 3) 
4293          self.assertAlmostEqual(spin71.chi2, 182.60081909193, 3) 
4294   
4295          # The 'CR72' model checks. 
4296          self.interpreter.pipe.switch(pipe_name='CR72 - relax_disp') 
4297          spin4 = return_spin(":4") 
4298          spin70 = return_spin(":70") 
4299          spin71 = return_spin(":71") 
4300          print("\n\nOptimised parameters:\n") 
4301          print("%-20s %-20s %-20s %-20s" % ("Parameter", "Value (:4)", "Value (:70)", "Value (:71)")) 
4302          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin4.r2[r20_key1], spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4303          print("%-20s %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin4.r2[r20_key2], spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4304          print("%-20s %20.15g %20.15g %20.15g" % ("pA", spin4.pA, spin70.pA, spin71.pA)) 
4305          print("%-20s %20.15g %20.15g %20.15g" % ("dw", spin4.dw, spin70.dw, spin71.dw)) 
4306          print("%-20s %20.15g %20.15g %20.15g" % ("kex", spin4.kex, spin70.kex, spin71.kex)) 
4307          print("%-20s %20.15g %20.15g %20.15g\n" % ("chi2", spin4.chi2, spin70.chi2, spin71.chi2)) 
4308          self.assertAlmostEqual(spin4.r2[r20_key1], 1.60463650370664, 2) 
4309          self.assertAlmostEqual(spin4.r2[r20_key2], 1.63221675941434, 3) 
4310          #self.assertAlmostEqual(spin4.pA, 0.818979078699935, 3)    # As dw (and kex) is zero, this parameter is not stable. 
4311          self.assertAlmostEqual(spin4.dw, 0.0, 2) 
4312          self.assertAlmostEqual(spin4.kex/10000, 0.0, 3) 
4313          self.assertAlmostEqual(spin4.chi2/100, 26.7356711142038/100, 3) 
4314          self.assertAlmostEqual(spin70.r2[r20_key1], 6.97268077496405, 3) 
4315          self.assertAlmostEqual(spin70.r2[r20_key2], 9.41028133407727, 3) 
4316          self.assertAlmostEqual(spin70.pA, 0.989856641885939, 3) 
4317          self.assertAlmostEqual(spin70.dw, 5.60889911049405, 3) 
4318          self.assertAlmostEqual(spin70.kex/10000, 1752.62025618632/10000, 3) 
4319          self.assertAlmostEqual(spin70.chi2, 53.8382196964083, 3) 
4320          self.assertAlmostEqual(spin71.r2[r20_key1], 4.98123328466942, 3) 
4321          self.assertAlmostEqual(spin71.pA, 0.996607425484157, 3) 
4322          self.assertAlmostEqual(spin71.dw, 4.34346257383825, 2) 
4323          self.assertAlmostEqual(spin71.kex/10000, 1936.73197158804/10000, 3) 
4324          self.assertAlmostEqual(spin71.chi2, 5.51703791653689, 3) 
4325   
4326   
4327 -    def test_hansen_cpmg_data_to_cr72(self): 
4328          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 dispersion model. 
4329   
4330          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4331          """ 
4332   
4333          # Base data setup. 
4334          self.setup_hansen_cpmg_data(model='CR72') 
4335   
4336          # Alias the spins. 
4337          spin70 = return_spin(":70") 
4338          spin71 = return_spin(":71") 
4339   
4340          # The R20 keys. 
4341          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4342          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4343   
4344          # Set the initial parameter values. 
4345          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4346          spin70.pA = 0.9 
4347          spin70.dw = 6.0 
4348          spin70.kex = 1500.0 
4349          spin71.r2 = {r20_key1: 5, r20_key2: 9.0} 
4350          spin71.pA = 0.9 
4351          spin71.dw = 4.0 
4352          spin71.kex = 1900.0 
4353   
4354          # Low precision optimisation. 
4355          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4356   
4357          # Printout. 
4358          print("\n\nOptimised parameters:\n") 
4359          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4360          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4361          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4362          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4363          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4364          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4365          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4366   
4367          # Checks for residue :70. 
4368          self.assertAlmostEqual(spin70.r2[r20_key1], 6.9724581325007, 4) 
4369          self.assertAlmostEqual(spin70.r2[r20_key2], 9.40968331038162, 2) 
4370          self.assertAlmostEqual(spin70.pA, 0.989856656702431, 4) 
4371          self.assertAlmostEqual(spin70.dw, 5.60885879594746, 3) 
4372          self.assertAlmostEqual(spin70.kex/1000, 1752.91052702273/1000, 3) 
4373          self.assertAlmostEqual(spin70.chi2, 53.8382133597495, 4) 
4374   
4375          # Checks for residue :71. 
4376          self.assertAlmostEqual(spin71.r2[r20_key1], 5.0030740940524, 4) 
4377          self.assertAlmostEqual(spin71.pA, 0.985941082507823, 4) 
4378          self.assertAlmostEqual(spin71.dw, 2.00640384113696, 4) 
4379          self.assertAlmostEqual(spin71.kex/1000, 2480.79614442041/1000, 4) 
4380          self.assertAlmostEqual(spin71.chi2, 15.6595388312451, 4) 
4381   
4382          # Test the conversion to k_AB from kex and pA. 
4383          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4384          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4385   
4386          # Test the conversion to k_BA from kex and pA. 
4387          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4388          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4389   
4390   
4391 -    def test_hansen_cpmg_data_to_cr72_full(self): 
4392          """Optimisation of Dr. Flemming Hansen's CPMG data to the CR72 full dispersion model. 
4393   
4394          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4395          """ 
4396   
4397          # Base data setup. 
4398          self.setup_hansen_cpmg_data(model='CR72 full') 
4399   
4400          # Alias the spins. 
4401          spin70 = return_spin(":70") 
4402          spin71 = return_spin(":71") 
4403   
4404          # The R20 keys. 
4405          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4406          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4407   
4408          # Set the initial parameter values. 
4409          spin70.r2a = {r20_key1: 7.0, r20_key2: 9.0} 
4410          spin70.r2b = {r20_key1: 7.0, r20_key2: 9.0} 
4411          spin70.pA = 0.9 
4412          spin70.dw = 6.0 
4413          spin70.kex = 1500.0 
4414          spin71.r2a = {r20_key1: 5.0, r20_key2: 9.0} 
4415          spin71.r2b = {r20_key1: 5.0, r20_key2: 9.0} 
4416          spin71.pA = 0.9 
4417          spin71.dw = 4.0 
4418          spin71.kex = 1900.0 
4419   
4420          # Low precision optimisation. 
4421          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4422   
4423          # Printout. 
4424          print("\n\nOptimised parameters:\n") 
4425          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4426          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4427          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4428          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4429          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4430          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4431          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4432          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4433          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4434   
4435          # Checks for residue :70. 
4436          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.87485258365614, 4) 
4437          self.assertAlmostEqual(spin70.r2b[r20_key1], 1.26075839074614, 4) 
4438          self.assertAlmostEqual(spin70.r2a[r20_key2], 8.79580446260797, 4) 
4439          self.assertAlmostEqual(spin70.r2b[r20_key2], 51.188411562843, 4) 
4440          self.assertAlmostEqual(spin70.pA, 0.989384178573802, 4) 
4441          self.assertAlmostEqual(spin70.dw, 5.54738203723682, 4) 
4442          self.assertAlmostEqual(spin70.kex/1000, 1831.4566463179/1000, 4) 
4443          self.assertAlmostEqual(spin70.chi2, 50.450410782403, 4) 
4444   
4445          # Checks for residue :71. 
4446          self.assertAlmostEqual(spin71.r2a[r20_key1], 5.04185695754972, 4) 
4447          self.assertAlmostEqual(spin71.r2b[r20_key1], 1.62857899941921, 4) 
4448          self.assertAlmostEqual(spin71.pA, 0.988832866751676, 4) 
4449          self.assertAlmostEqual(spin71.dw, 2.24905251856265, 4) 
4450          self.assertAlmostEqual(spin71.kex/1000, 2397.64122642946/1000, 4) 
4451          self.assertAlmostEqual(spin71.chi2, 15.8586492923672, 4) 
4452   
4453          # Test the conversion to k_AB from kex and pA. 
4454          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4455          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4456   
4457          # Test the conversion to k_BA from kex and pA. 
4458          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4459          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4460   
4461   
4462 -    def test_hansen_cpmg_data_to_it99(self): 
4463          """Optimisation of Dr. Flemming Hansen's CPMG data to the IT99 dispersion model. 
4464   
4465          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4466          """ 
4467   
4468          # Base data setup. 
4469          self.setup_hansen_cpmg_data(model='IT99') 
4470   
4471          # Alias the spins. 
4472          spin70 = return_spin(":70") 
4473          spin71 = return_spin(":71") 
4474   
4475          # The R20 keys. 
4476          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4477          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4478   
4479          # Set the initial parameter values. 
4480          spin70.r2 = {r20_key1: 8.8, r20_key2: 16.6} 
4481          spin70.dw = 10.0 
4482          spin70.pA = 0.5 
4483          spin70.tex = 1000.09 
4484          spin71.r2 = {r20_key1: 1.0, r20_key2: 1.0} 
4485          spin71.dw = 10.0 
4486          spin71.pA = 0.95 
4487          spin71.tex = 0.1 
4488   
4489          # Low precision optimisation. 
4490          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-10, grad_tol=None, max_iter=10000, constraints=True, scaling=True, verbosity=1) 
4491   
4492          # Printout. 
4493          print("\n\nOptimised parameters:\n") 
4494          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4495          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4496          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4497          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4498          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4499          print("%-20s %20.15g %20.15g" % ("tex", spin70.tex, spin71.tex)) 
4500          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4501   
4502          # Checks for residue :70. 
4503          self.assertAlmostEqual(spin70.r2[r20_key1], 7.24471197811838, 4) 
4504          self.assertAlmostEqual(spin70.r2[r20_key2], 10.0571040704729, 4) 
4505          self.assertAlmostEqual(spin70.dw, 5.2116923222744, 4) 
4506          self.assertAlmostEqual(spin70.pA, 0.990253627907212, 4) 
4507          self.assertAlmostEqual(spin70.tex*1000, 0.000638394793480444*1000, 4) 
4508          self.assertAlmostEqual(spin70.chi2, 93.5135798618747, 4) 
4509   
4510          # Checks for residue :71. 
4511          self.assertAlmostEqual(spin71.r2[r20_key1], 5.05971235970214, 4) 
4512          self.assertAlmostEqual(spin71.r2[r20_key2], 6.96641194493447, 4) 
4513          self.assertAlmostEqual(spin71.dw, 0.435389946897141, 4) 
4514          self.assertAlmostEqual(spin71.pA, 0.500000000213519, 3) 
4515          self.assertAlmostEqual(spin71.tex*1000, 0.000372436400585538*1000, 4) 
4516          self.assertAlmostEqual(spin71.chi2, 23.7895798801404, 4) 
4517   
4518   
4519 -    def test_hansen_cpmg_data_to_lm63(self): 
4520          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4521   
4522          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4523          """ 
4524   
4525          # Base data setup. 
4526          self.setup_hansen_cpmg_data(model='LM63') 
4527   
4528          # Alias the spins. 
4529          spin70 = return_spin(":70") 
4530          spin71 = return_spin(":71") 
4531   
4532          # The R20 keys. 
4533          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4534          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4535   
4536          # Set the initial parameter values. 
4537          spin70.r2 = {r20_key1: 7.0, r20_key2: 7.0} 
4538          spin70.phi_ex = 0.3 
4539          spin70.kex = 5000.0 
4540          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4541          spin71.phi_ex = 0.1 
4542          spin71.kex = 2500.0 
4543   
4544          # Low precision optimisation. 
4545          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4546   
4547          # Printout. 
4548          print("\n\nOptimised parameters:\n") 
4549          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4550          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4551          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4552          print("%-20s %20.15g %20.15g" % ("phi_ex", spin70.phi_ex, spin71.phi_ex)) 
4553          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4554          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4555   
4556          # Checks for residue :70. 
4557          self.assertAlmostEqual(spin70.r2[r20_key1], 6.74362294539099) 
4558          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406797067481, 6) 
4559          self.assertAlmostEqual(spin70.phi_ex, 0.312733013751449) 
4560          self.assertAlmostEqual(spin70.kex/1000, 4723.09897146338/1000, 6) 
4561          self.assertAlmostEqual(spin70.chi2, 363.534044873483) 
4562   
4563          # Checks for residue :71. 
4564          self.assertAlmostEqual(spin71.r2[r20_key1], 5.00776657729728, 5) 
4565          self.assertAlmostEqual(spin71.phi_ex, 0.0553787825650613, 5) 
4566          self.assertAlmostEqual(spin71.kex/1000, 2781.72292994154/1000, 5) 
4567          self.assertAlmostEqual(spin71.chi2, 17.0776399916287, 5) 
4568   
4569   
4570 -    def test_hansen_cpmg_data_to_lm63_3site(self): 
4571          """Optimisation of Dr. Flemming Hansen's CPMG data to the LM63 dispersion model. 
4572   
4573          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4574          """ 
4575   
4576          # Base data setup. 
4577          self.setup_hansen_cpmg_data(model='LM63 3-site') 
4578   
4579          # Alias the spins. 
4580          spin70 = return_spin(":70") 
4581          spin71 = return_spin(":71") 
4582   
4583          # The R20 keys. 
4584          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4585          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4586   
4587          ## Set the initial parameter values. 
4588          spin70.r2 = {r20_key1: 7.570370921220954, r20_key2: 8.694446951909107} 
4589          spin70.phi_ex_B = 0.14872003058250227 
4590          spin70.phi_ex_C = 0.1319419923472704 
4591          spin70.kB = 4103.672910444741 
4592          spin70.kC = 7029.001690726248 
4593          spin71.r2 = {r20_key1: 5.1347793381636, r20_key2: 7.156573986051575} 
4594          spin71.phi_ex_B = 0.04013553485505605 
4595          spin71.phi_ex_C = 0.020050748406928887 
4596          spin71.kB = 4045.3007136121364 
4597          spin71.kC = 3586.38798270774 
4598   
4599          #self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
4600          #self.interpreter.minimise.grid_search(lower=None, upper=None, inc=41, constraints=True, verbosity=1) 
4601   
4602          # Low precision optimisation. 
4603          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-25, grad_tol=None, max_iter=10000000, constraints=True, scaling=True, verbosity=1) 
4604   
4605          # Printout. 
4606          print("\n\nOptimised parameters:\n") 
4607          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4608          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4609          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4610          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin70.phi_ex_B, spin71.phi_ex_B)) 
4611          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin70.phi_ex_C, spin71.phi_ex_C)) 
4612          print("%-20s %20.15g %20.15g" % ("kB", spin70.kB, spin71.kB)) 
4613          print("%-20s %20.15g %20.15g" % ("kC", spin70.kC, spin71.kC)) 
4614          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4615   
4616          # Checks for residue :70. 
4617          self.assertAlmostEqual(spin70.r2[r20_key1], 6.7436230253685, 5) 
4618          self.assertAlmostEqual(spin70.r2[r20_key2], 6.57406813008828, 6) 
4619          self.assertAlmostEqual(spin70.phi_ex_B, 0.206304023079778, 5) 
4620          self.assertAlmostEqual(spin70.phi_ex_C, 0.106428983339627, 5) 
4621          self.assertAlmostEqual(spin70.kB/1000, 4723.09897652589/1000, 6) 
4622          self.assertAlmostEqual(spin70.kC/1000, 4723.09876196409/1000, 6) 
4623          self.assertAlmostEqual(spin70.chi2, 363.534044873483, 5) 
4624   
4625          # Checks for residue :71. 
4626          self.assertAlmostEqual(spin71.r2[r20_key1], 4.96612095596752, 5) 
4627          self.assertAlmostEqual(spin71.phi_ex_B, 0.00398262266512895, 5) 
4628          self.assertAlmostEqual(spin71.phi_ex_C, 0.0555791581291262, 5) 
4629          self.assertAlmostEqual(spin71.kB/1000, 1323.33195689832/1000, 5) 
4630          self.assertAlmostEqual(spin71.kC/1000, 3149.58971568059/1000, 5) 
4631          self.assertAlmostEqual(spin71.chi2, 16.2620934464368) 
4632   
4633   
4634 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D(self): 
4635          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D' dispersion model. 
4636   
4637          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4638          """ 
4639   
4640          # Base data setup. 
4641          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D') 
4642   
4643          # Alias the spins. 
4644          spin70 = return_spin(":70") 
4645          spin71 = return_spin(":71") 
4646   
4647          # The R20 keys. 
4648          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4649          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4650   
4651          # Set the initial parameter values. 
4652          spin70.r2 = {r20_key1: 6.994165925, r20_key2: 9.428129427} 
4653          spin70.pA = 0.9897754407 
4654          spin70.dw = 5.642418428 
4655          spin70.kex = 1743.666375 
4656          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4657          spin71.pA = 0.9968032899 
4658          spin71.dw = 4.577891393 
4659          spin71.kex = 1830.044597 
4660   
4661          # Low precision optimisation. 
4662          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4663   
4664          # Printout. 
4665          print("\n\nOptimised parameters:\n") 
4666          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4667          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4668          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4669          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4670          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4671          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4672          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4673   
4674          # Checks for residue :70. 
4675          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95797760459016, 4) 
4676          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39628959312699, 4) 
4677          self.assertAlmostEqual(spin70.pA, 0.989700985380975, 4) 
4678          self.assertAlmostEqual(spin70.dw, 5.6733714171086, 4) 
4679          self.assertAlmostEqual(spin70.kex/1000, 1713.63101361545/1000, 4) 
4680          self.assertAlmostEqual(spin70.chi2, 52.5106928523775, 4) 
4681   
4682          # Checks for residue :71. 
4683          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99893565849977, 4) 
4684          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89825625944034, 4) 
4685          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 4) 
4686          self.assertAlmostEqual(spin71.dw, 2.09292495350993, 4) 
4687          self.assertAlmostEqual(spin71.kex/1000, 2438.04423541463/1000, 4) 
4688          self.assertAlmostEqual(spin71.chi2, 15.164490242352, 4) 
4689   
4690          # Test the conversion to k_AB from kex and pA. 
4691          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4692          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4693   
4694          # Test the conversion to k_BA from kex and pA. 
4695          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4696          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4697   
4698   
4699 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_3D_full(self): 
4700          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site 3D full' dispersion model. 
4701   
4702          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4703          """ 
4704   
4705          # Base data setup. 
4706          self.setup_hansen_cpmg_data(model='NS CPMG 2-site 3D full') 
4707   
4708          # Alias the spins. 
4709          spin70 = return_spin(":70") 
4710          spin71 = return_spin(":71") 
4711   
4712          # The R20 keys. 
4713          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4714          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4715   
4716          # Set the initial parameter values. 
4717          spin70.r2a = {r20_key1: 6.644753428, r20_key2: 7.891776687} 
4718          spin70.r2b = {r20_key1: 7.163478485, r20_key2: 138.5170395} 
4719          spin70.pA = 0.9884781357 
4720          spin70.dw = 5.456507396 
4721          spin70.kex = 1906.521189 
4722          spin71.r2a = {r20_key1: 4.99893524108981, r20_key2: 100.0} 
4723          spin71.r2b = {r20_key1: 8.27456243639973, r20_key2: 100.0} 
4724          spin71.pA = 0.986709616684097 
4725          spin71.dw = 2.09245158280905 
4726          spin71.kex = 2438.2766211401 
4727   
4728          # Low precision optimisation. 
4729          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4730   
4731          # Printout. 
4732          print("\n\nOptimised parameters:\n") 
4733          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4734          print("%-20s %20.15g %20.15g" % ("R2A (500 MHz)", spin70.r2a[r20_key1], spin71.r2a[r20_key1])) 
4735          print("%-20s %20.15g %20.15g" % ("R2B (500 MHz)", spin70.r2b[r20_key1], spin71.r2b[r20_key1])) 
4736          print("%-20s %20.15g %20.15g" % ("R2A (800 MHz)", spin70.r2a[r20_key2], spin71.r2a[r20_key2])) 
4737          print("%-20s %20.15g %20.15g" % ("R2B (800 MHz)", spin70.r2b[r20_key2], spin71.r2b[r20_key2])) 
4738          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4739          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4740          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4741          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4742   
4743          # Checks for residue :70. 
4744          self.assertAlmostEqual(spin70.r2a[r20_key1], 6.61176004043484, 4) 
4745          self.assertAlmostEqual(spin70.r2b[r20_key1], 7.4869316381241, 4) 
4746          self.assertAlmostEqual(spin70.r2a[r20_key2], 7.78200386067591, 4) 
4747          self.assertAlmostEqual(spin70.r2b[r20_key2], 141.703593742468, 4) 
4748          self.assertAlmostEqual(spin70.pA, 0.988404987055969, 4) 
4749          self.assertAlmostEqual(spin70.dw, 5.4497360203213, 4) 
4750          self.assertAlmostEqual(spin70.kex/1000, 1934.09304607082/1000, 4) 
4751          self.assertAlmostEqual(spin70.chi2, 44.6793752187925, 4) 
4752   
4753          # Checks for residue :71. 
4754          self.assertAlmostEqual(spin71.r2a[r20_key1], 4.6013095731966, 4) 
4755          self.assertAlmostEqual(spin71.r2b[r20_key1], 13.3245678276332, 4) 
4756          self.assertAlmostEqual(spin71.r2a[r20_key2], 2.08243621257779, 4) 
4757          self.assertAlmostEqual(spin71.r2b[r20_key2], 153.355765094575, 4) 
4758          self.assertAlmostEqual(spin71.pA, 0.9665748685124, 4) 
4759          self.assertAlmostEqual(spin71.dw, 1.41898001408953, 4) 
4760          self.assertAlmostEqual(spin71.kex/1000, 2580.65795560688/1000, 4) 
4761          self.assertAlmostEqual(spin71.chi2, 13.4937006732165, 4) 
4762   
4763          # Test the conversion to k_AB from kex and pA. 
4764          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4765          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4766   
4767          # Test the conversion to k_BA from kex and pA. 
4768          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4769          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4770   
4771   
4772 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_expanded(self): 
4773          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site expanded' dispersion model. 
4774   
4775          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4776          """ 
4777   
4778          # Base data setup. 
4779          self.setup_hansen_cpmg_data(model='NS CPMG 2-site expanded') 
4780   
4781          # Alias the spins. 
4782          spin70 = return_spin(":70") 
4783          spin71 = return_spin(":71") 
4784   
4785          # The R20 keys. 
4786          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4787          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4788   
4789          # Set the initial parameter values. 
4790          spin70.r2 = {r20_key1: 7.0, r20_key2: 9.0} 
4791          spin70.pA = 0.9 
4792          spin70.dw = 6.0 
4793          spin70.kex = 1500.0 
4794          spin71.r2 = {r20_key1: 5.0, r20_key2: 9.0} 
4795          spin71.pA = 0.9 
4796          spin71.dw = 4.0 
4797          spin71.kex = 1900.0 
4798   
4799          # Low precision optimisation. 
4800          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
4801   
4802          # Printout. 
4803          print("\n\nOptimised parameters:\n") 
4804          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4805          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4806          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4807          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4808          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4809          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4810          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4811   
4812          # Checks for residue :70. 
4813          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95813330991529, 4) 
4814          self.assertAlmostEqual(spin70.r2[r20_key2], 9.39663480561524, 4) 
4815          self.assertAlmostEqual(spin70.pA, 0.989700843879574, 4) 
4816          self.assertAlmostEqual(spin70.dw, 5.67315878825691, 4) 
4817          self.assertAlmostEqual(spin70.kex/1000, 1713.56110716632/1000, 4) 
4818          self.assertAlmostEqual(spin70.chi2, 52.5106879242812, 4) 
4819   
4820          # Checks for residue :71. 
4821          self.assertAlmostEqual(spin71.r2[r20_key1], 4.99881666793312, 4) 
4822          self.assertAlmostEqual(spin71.r2[r20_key2], 6.89817482453042, 4) 
4823          self.assertAlmostEqual(spin71.pA, 0.986712911453639, 4) 
4824          self.assertAlmostEqual(spin71.dw, 2.09273069372236, 4) 
4825          self.assertAlmostEqual(spin71.kex/1000, 2438.20525930405/1000, 4) 
4826          self.assertAlmostEqual(spin71.chi2, 15.1644913030633, 4) 
4827   
4828          # Test the conversion to k_AB from kex and pA. 
4829          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4830          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4831   
4832          # Test the conversion to k_BA from kex and pA. 
4833          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4834          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4835   
4836   
4837 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star(self): 
4838          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star' dispersion model. 
4839   
4840          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4841          """ 
4842   
4843          # Base data setup. 
4844          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star') 
4845   
4846          # Alias the spins. 
4847          spin70 = return_spin(":70") 
4848          spin71 = return_spin(":71") 
4849   
4850          # The R20 keys. 
4851          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4852          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4853   
4854          # Set the initial parameter values. 
4855          spin70.r2 = {r20_key1: 6.996327746, r20_key2: 9.452051268} 
4856          spin70.pA = 0.9897519798 
4857          spin70.dw = 5.644862195 
4858          spin70.kex = 1723.820567 
4859          spin71.r2 = {r20_key1: 4.978654237, r20_key2: 9.276918959} 
4860          spin71.pA = 0.9968032899 
4861          spin71.dw = 4.577891393 
4862          spin71.kex = 1830.044597 
4863   
4864          # Low precision optimisation. 
4865          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=False, scaling=True, verbosity=1) 
4866   
4867          # Printout. 
4868          print("\n\nOptimised parameters:\n") 
4869          print("%-20s %-20s %-20s" % ("Parameter", "Value (:70)", "Value (:71)")) 
4870          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin70.r2[r20_key1], spin71.r2[r20_key1])) 
4871          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin70.r2[r20_key2], spin71.r2[r20_key2])) 
4872          print("%-20s %20.15g %20.15g" % ("pA", spin70.pA, spin71.pA)) 
4873          print("%-20s %20.15g %20.15g" % ("dw", spin70.dw, spin71.dw)) 
4874          print("%-20s %20.15g %20.15g" % ("kex", spin70.kex, spin71.kex)) 
4875          print("%-20s %20.15g %20.15g\n" % ("chi2", spin70.chi2, spin71.chi2)) 
4876   
4877          # Checks for residue :70. 
4878          self.assertAlmostEqual(spin70.r2[r20_key1], 6.95543947938561, 1) 
4879          self.assertAlmostEqual(spin70.r2[r20_key2], 9.38991914134929, 1) 
4880          self.assertAlmostEqual(spin70.pA, 0.989702750971153, 3) 
4881          self.assertAlmostEqual(spin70.dw, 5.67527122494516, 1) 
4882          self.assertAlmostEqual(spin70.kex/1000, 1715.72032391817/1000, 1) 
4883          self.assertAlmostEqual(spin70.chi2, 52.5011991483842, 1) 
4884   
4885          # Checks for residue :71. 
4886          self.assertAlmostEqual(spin71.r2[r20_key1], 4.992594256544, 1) 
4887          self.assertAlmostEqual(spin71.pA, 0.986716058519642, 2) 
4888          self.assertAlmostEqual(spin71.dw/100, 2.09292495350993/100, 2) 
4889          self.assertAlmostEqual(spin71.kex/100000, 2438.04423541463/100000, 2) 
4890          self.assertAlmostEqual(spin71.chi2/100, 15.1644902423334/100, 1) 
4891   
4892          # Test the conversion to k_AB from kex and pA. 
4893          self.assertEqual(spin70.k_AB, spin70.kex * (1.0 - spin70.pA)) 
4894          self.assertEqual(spin71.k_AB, spin71.kex * (1.0 - spin71.pA)) 
4895   
4896          # Test the conversion to k_BA from kex and pA. 
4897          self.assertEqual(spin70.k_BA, spin70.kex * spin70.pA) 
4898          self.assertEqual(spin71.k_BA, spin71.kex * spin71.pA) 
4899   
4900   
4901 -    def test_hansen_cpmg_data_to_ns_cpmg_2site_star_full(self): 
4902          """Optimisation of Dr. Flemming Hansen's CPMG data to the 'NS CPMG 2-site star full' dispersion model. 
4903   
4904          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4905          """ 
4906   
4907          # Base data setup. 
4908          self.setup_hansen_cpmg_data(model='NS CPMG 2-site star full') 
4909   
4910          # Alias the spins. 
4911          spin70 = return_spin(":70") 
4912          spin71 = return_spin(":71") 
4913   
4914          # The R20 keys. 
4915          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
4916          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
4917   
4918          # Set the initial parameter values. 
4919          spin70.r2a = {r20_key1: 6.44836878645126, r20_key2: 7.00382877393494} 
4920          spin70.r2b = {r20_key1: 12.2083127421994, r20_key2: 199.862962628402} 
4921          spin70.pA = 0.987648082613451 
4922          spin70.dw = 5.30679853807572 
4923          spin70.kex = 2033.25380420666 
4924          spin71.r2a = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4925          spin71.r2b = {r20_key1: 4.992594256544, r20_key2: 6.98674718938435} 
4926          spin71.pA = 0.992258541625787 
4927          spin71.dw = 2.75140650899058 
4928          spin71.kex = 2106.60885247431 
4929   
4930          # Low precision optimisation. 
4931          self.interpreter.minimise.calculate() 
4932   
4933          # Checks for residue :70. 
4934          self.assertAlmostEqual(spin70.chi2/10, 45.773987568491123/10, 2) 
4935          self.assertAlmostEqual(spin71.chi2/10, 17.329385665659192/10, 2) 
4936   
4937   
4938 -    def test_hansen_cpmgfit_input(self): 
4939          """Conversion of Dr. Flemming Hansen's CPMG R2eff values into input files for CPMGFit. 
4940   
4941          This uses the data from Dr. Flemming Hansen's paper at http://dx.doi.org/10.1021/jp074793o.  This is CPMG data with a fixed relaxation time period. 
4942          """ 
4943   
4944          # Load the R2eff results file. 
4945          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'r2eff_pipe' 
4946          self.interpreter.results.read(file_name) 
4947          self.interpreter.deselect.spin(':4') 
4948   
4949          # Set up the model. 
4950          self.interpreter.relax_disp.select_model('LM63') 
4951   
4952          # Generate the input files. 
4953          self.interpreter.relax_disp.cpmgfit_input(force=True, dir=ds.tmpdir) 
4954   
4955          # What the files should contain. 
4956          batch_file = ['#! /bin/sh\n', '\n', 'cpmgfit -grid -xmgr -f spin_70_N.in | tee spin_70_N.out\n', 'cpmgfit -grid -xmgr -f spin_71_N.in | tee spin_71_N.out\n'] 
4957          spin1 = [ 
4958              "title :70@N\n", 
4959              "fields 2 11.7432964915 18.7892743865\n", 
4960              "function CPMG\n", 
4961              "R2 1 10 20\n", 
4962              "Rex 0 100.0 100\n", 
4963              "Tau 0 10.0 100\n", 
4964              "xmgr\n", 
4965              "@ xaxis label \"1/tcp (1/ms)\"\n", 
4966              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
4967              "@ xaxis ticklabel format decimal\n", 
4968              "@ yaxis ticklabel format decimal\n", 
4969              "@ xaxis ticklabel char size 0.8\n", 
4970              "@ yaxis ticklabel char size 0.8\n", 
4971              "@ world xmin 0.0\n", 
4972              "data\n", 
4973              "0.133333             16.045541            0.310925             11.743296           \n", 
4974              "0.266667             14.877925            0.303217             11.743296           \n", 
4975              "0.400000             14.357820            0.299894             11.743296           \n", 
4976              "0.533333             12.664495            0.289532             11.743296           \n", 
4977              "0.666667             12.363205            0.287760             11.743296           \n", 
4978              "0.800000             11.092532            0.280514             11.743296           \n", 
4979              "0.933333             10.566090            0.277619             11.743296           \n", 
4980              "1.066667             9.805807             0.273544             11.743296           \n", 
4981              "1.200000             9.564301             0.272276             11.743296           \n", 
4982              "1.333333             9.015634             0.269442             11.743296           \n", 
4983              "1.466667             8.607765             0.267375             11.743296           \n", 
4984              "1.600000             8.279997             0.265740             11.743296           \n", 
4985              "1.733333             8.474536             0.266708             11.743296           \n", 
4986              "1.866667             8.158973             0.265141             11.743296           \n", 
4987              "2.000000             7.988631             0.264304             11.743296           \n", 
4988              "0.133333             22.224914            0.166231             18.789274           \n", 
4989              "0.266667             21.230874            0.162377             18.789274           \n", 
4990              "0.400000             20.603704            0.160017             18.789274           \n", 
4991              "0.533333             20.327797            0.158996             18.789274           \n", 
4992              "0.666667             18.855377            0.153719             18.789274           \n", 
4993              "0.800000             18.537531            0.152617             18.789274           \n", 
4994              "0.933333             17.508069            0.149138             18.789274           \n", 
4995              "1.066667             16.035604            0.144391             18.789274           \n", 
4996              "1.200000             15.168192            0.141717             18.789274           \n", 
4997              "1.333333             14.431802            0.139516             18.789274           \n", 
4998              "1.466667             14.034137            0.138354             18.789274           \n", 
4999              "1.600000             12.920148            0.135192             18.789274           \n", 
5000              "1.733333             12.653673            0.134456             18.789274           \n", 
5001              "1.866667             12.610864            0.134338             18.789274           \n", 
5002              "2.000000             11.969303            0.132601             18.789274           \n" 
5003          ] 
5004          spin2 = [ 
5005              "title :71@N\n", 
5006              "fields 2 11.7432964915 18.7892743865\n", 
5007              "function CPMG\n", 
5008              "R2 1 10 20\n", 
5009              "Rex 0 100.0 100\n", 
5010              "Tau 0 10.0 100\n", 
5011              "xmgr\n", 
5012              "@ xaxis label \"1/tcp (1/ms)\"\n", 
5013              "@ yaxis label \"R2(tcp) (rad/s)\"\n", 
5014              "@ xaxis ticklabel format decimal\n", 
5015              "@ yaxis ticklabel format decimal\n", 
5016              "@ xaxis ticklabel char size 0.8\n", 
5017              "@ yaxis ticklabel char size 0.8\n", 
5018              "@ world xmin 0.0\n", 
5019              "data\n", 
5020              "0.133333             7.044342             0.170035             11.743296           \n", 
5021              "0.266667             6.781033             0.169228             11.743296           \n", 
5022              "0.400000             6.467623             0.168279             11.743296           \n", 
5023              "0.533333             6.333340             0.167876             11.743296           \n", 
5024              "0.666667             6.323238             0.167846             11.743296           \n", 
5025              "0.800000             6.005245             0.166902             11.743296           \n", 
5026              "0.933333             5.767052             0.166203             11.743296           \n", 
5027              "1.066667             5.476968             0.165361             11.743296           \n", 
5028              "1.200000             5.469949             0.165341             11.743296           \n", 
5029              "1.333333             5.295113             0.164838             11.743296           \n", 
5030              "1.466667             5.435648             0.165242             11.743296           \n", 
5031              "1.600000             5.410400             0.165169             11.743296           \n", 
5032              "1.733333             5.437554             0.165247             11.743296           \n", 
5033              "1.866667             5.176844             0.164501             11.743296           \n", 
5034              "2.000000             5.227232             0.164644             11.743296           \n", 
5035              "0.133333             11.530903            0.081928             18.789274           \n", 
5036              "0.266667             10.983094            0.081041             18.789274           \n", 
5037              "0.400000             10.512403            0.080294             18.789274           \n", 
5038              "0.533333             9.984805             0.079473             18.789274           \n", 
5039              "0.666667             9.573163             0.078845             18.789274           \n", 
5040              "0.800000             9.178810             0.078253             18.789274           \n", 
5041              "0.933333             8.935719             0.077893             18.789274           \n", 
5042              "1.066667             8.610147             0.077416             18.789274           \n", 
5043              "1.200000             8.353778             0.077045             18.789274           \n", 
5044              "1.333333             8.173729             0.076787             18.789274           \n", 
5045              "1.466667             8.091607             0.076670             18.789274           \n", 
5046              "1.600000             7.706420             0.076126             18.789274           \n", 
5047              "1.733333             7.709125             0.076129             18.789274           \n", 
5048              "1.866667             7.610856             0.075992             18.789274           \n", 
5049              "2.000000             7.552584             0.075911             18.789274           \n", 
5050          ] 
5051   
5052          # Check the batch file. 
5053          print("\nChecking the batch file.") 
5054          file = open("%s%sbatch_run.sh" % (ds.tmpdir, sep)) 
5055          lines = file.readlines() 
5056          file.close() 
5057          for i in range(len(lines)): 
5058              self.assertEqual(batch_file[i], lines[i]) 
5059   
5060          # Check spin :70@N. 
5061          print("\nChecking the spin :70@N input file.") 
5062          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_70_N')) 
5063          lines = file.readlines() 
5064          file.close() 
5065          for i in range(len(spin1)): 
5066              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
5067          for i in range(len(lines)): 
5068              self.assertEqual(spin1[i], lines[i]) 
5069   
5070          # Check spin :71@N. 
5071          print("\nChecking the spin :71@N input file.") 
5072          file = open("%s%sspin%s.in" % (ds.tmpdir, sep, '_71_N')) 
5073          lines = file.readlines() 
5074          file.close() 
5075          for i in range(len(lines)): 
5076              print("%s\"%s\\n\"," % (" "*12, lines[i][:-1])) 
5077          for i in range(len(spin2)): 
5078              self.assertEqual(spin2[i], lines[i]) 
5079   
5080   
5081 -    def test_korzhnev_2005_15n_dq_data(self): 
5082          """Optimisation of the Korzhnev et al., 2005 15N DQ CPMG data using the 'NS MMQ 2-site' model. 
5083   
5084          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5085   
5086          Here only the 15N DQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5087   
5088              - r2 = {'500': 9.487269007171426, '600': 11.718267257562591, '800': 13.624551743116887}, 
5089              - pA = 0.965402506690231, 
5090              - dw = 0.805197170133360, 
5091              - dwH = -0.595536627771890, 
5092              - kex = 569.003663067619868, 
5093              - chi2 = 9.297671357952812. 
5094          """ 
5095   
5096          # Base data setup. 
5097          self.setup_korzhnev_2005_data(data_list=['DQ']) 
5098   
5099          # Alias the spin. 
5100          spin = return_spin(":9@N") 
5101   
5102          # The R20 keys. 
5103          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5104          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5105          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5106   
5107          # Set the initial parameter values. 
5108          spin.r2 = {r20_key1: 9.48527908326952, r20_key2: 11.7135951595536, r20_key3: 13.6153887849344} 
5109          spin.pA = 0.965638501551899 
5110          spin.dw = 2.8537583461577 
5111          spin.dwH = -0.387633062766635 
5112          spin.kex = 573.704033851592 
5113   
5114          # Low precision optimisation. 
5115          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5116   
5117          # Monte Carlo simulations. 
5118          self.interpreter.monte_carlo.setup(number=3) 
5119          self.interpreter.monte_carlo.create_data(method='back_calc') 
5120          self.interpreter.monte_carlo.initial_values() 
5121          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5122          self.interpreter.monte_carlo.error_analysis() 
5123   
5124          # Plot the dispersion curves. 
5125          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5126   
5127          # Save the results. 
5128          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5129   
5130          # Printout. 
5131          print("\n\nOptimised parameters:\n") 
5132          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5133          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5134          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5135          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5136          print("%-20s %20.15g" % ("pA", spin.pA)) 
5137          print("%-20s %20.15g" % ("dw", spin.dw)) 
5138          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5139          print("%-20s %20.15g" % ("kex", spin.kex)) 
5140          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5141   
5142          # Checks for residue :9. 
5143          self.assertAlmostEqual(spin.r2[r20_key1], 9.4870656457415, 2) 
5144          self.assertAlmostEqual(spin.r2[r20_key2], 11.7183291788929, 2) 
5145          self.assertAlmostEqual(spin.r2[r20_key3], 13.6241729933153, 2) 
5146          self.assertAlmostEqual(spin.pA, 0.965405468217295, 4) 
5147          self.assertAlmostEqual(spin.dw, 2.76835528427355, 1) 
5148          self.assertAlmostEqual(spin.dwH, -0.396489341086363, 2) 
5149          self.assertAlmostEqual(spin.kex/1000, 569.06937047601/1000, 3) 
5150          self.assertAlmostEqual(spin.chi2, 9.29767487125257, 2) 
5151   
5152   
5153 -    def test_korzhnev_2005_15n_mq_data(self): 
5154          """Optimisation of the Korzhnev et al., 2005 15N MQ CPMG data using the 'NS MMQ 2-site' model. 
5155   
5156          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5157   
5158          Here only the 15N MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5159   
5160              - r2 = {'500': 5.993083514798655, '600': 6.622184438384841, '800': 8.640765919352019}, 
5161              - pA = 0.930027999814003, 
5162              - dw = 4.338620619954370, 
5163              - dwH = -0.274250775560818, 
5164              - kex = 344.613362916544475, 
5165              - chi2 = 10.367733168217050. 
5166          """ 
5167   
5168          # Base data setup. 
5169          self.setup_korzhnev_2005_data(data_list=['MQ']) 
5170   
5171          # Alias the spin. 
5172          spin = return_spin(":9@N") 
5173   
5174          # The R20 keys. 
5175          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5176          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5177          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5178   
5179          # Set the initial parameter values. 
5180          spin.r2 = {r20_key1: 6.02016436619016, r20_key2: 6.65421500772308, r20_key3: 8.6729591487622} 
5181          spin.pA = 0.930083249288083 
5182          spin.dw = 4.33890689462363 
5183          spin.dwH = -0.274316585638047 
5184          spin.kex = 344.329651956132 
5185   
5186          # Low precision optimisation. 
5187          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5188   
5189          # Monte Carlo simulations. 
5190          self.interpreter.monte_carlo.setup(number=3) 
5191          self.interpreter.monte_carlo.create_data(method='back_calc') 
5192          self.interpreter.monte_carlo.initial_values() 
5193          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5194          self.interpreter.monte_carlo.error_analysis() 
5195   
5196          # Plot the dispersion curves. 
5197          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5198   
5199          # Save the results. 
5200          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5201   
5202          # Printout. 
5203          print("\n\nOptimised parameters:\n") 
5204          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5205          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5206          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5207          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5208          print("%-20s %20.15g" % ("pA", spin.pA)) 
5209          print("%-20s %20.15g" % ("dw", spin.dw)) 
5210          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5211          print("%-20s %20.15g" % ("kex", spin.kex)) 
5212          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5213   
5214          # Checks for residue :9. 
5215          self.assertAlmostEqual(spin.r2[r20_key1], 5.99503641023038, 1) 
5216          self.assertAlmostEqual(spin.r2[r20_key2], 6.62432897608527, 1) 
5217          self.assertAlmostEqual(spin.r2[r20_key3], 8.64278915809492, 1) 
5218          self.assertAlmostEqual(spin.pA, 0.930036474040713, 3) 
5219          self.assertAlmostEqual(spin.dw, 4.33848403058432, 2) 
5220          self.assertAlmostEqual(spin.dwH, -0.274246558825267, 3) 
5221          self.assertAlmostEqual(spin.kex/1000, 344.626563267384/1000, 3) 
5222          self.assertAlmostEqual(spin.chi2, 10.3677362372789, 2) 
5223   
5224   
5225 -    def test_korzhnev_2005_15n_sq_data(self): 
5226          """Optimisation of the Korzhnev et al., 2005 15N SQ CPMG data using the 'NS MMQ 2-site' model. 
5227   
5228          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5229   
5230          Here only the 15N SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5231   
5232              - r2 = {'500': 8.335037972570017, '600': 8.761366016417508, '800': 10.225001019091822}, 
5233              - pA = 0.950003458294991, 
5234              - dw = 4.358402855315123, 
5235              - kex = 429.906473361926999, 
5236              - chi2 = 17.393331915567252. 
5237          """ 
5238   
5239          # Base data setup. 
5240          self.setup_korzhnev_2005_data(data_list=['SQ']) 
5241   
5242          # Alias the spin. 
5243          spin = return_spin(":9@N") 
5244   
5245          # The R20 keys. 
5246          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5247          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5248          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5249   
5250          # Set the initial parameter values. 
5251          spin.r2 = {r20_key1: 8.334232330326190, r20_key2: 8.756773997879968, r20_key3: 10.219320492033058} 
5252          spin.pA = 0.950310172115387 
5253          spin.dw = 4.356737157889636 
5254          spin.kex = 433.176323890829849 
5255   
5256          # Low precision optimisation. 
5257          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5258   
5259          # Monte Carlo simulations. 
5260          self.interpreter.monte_carlo.setup(number=3) 
5261          self.interpreter.monte_carlo.create_data(method='back_calc') 
5262          self.interpreter.monte_carlo.initial_values() 
5263          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5264          self.interpreter.monte_carlo.error_analysis() 
5265   
5266          # Plot the dispersion curves. 
5267          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5268   
5269          # Save the results. 
5270          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5271   
5272          # Printout. 
5273          print("\n\nOptimised parameters:\n") 
5274          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5275          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5276          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5277          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5278          print("%-20s %20.15g" % ("pA", spin.pA)) 
5279          print("%-20s %20.15g" % ("dw", spin.dw)) 
5280          print("%-20s %20.15g" % ("kex", spin.kex)) 
5281          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5282   
5283          # Checks for residue :9. 
5284          self.assertAlmostEqual(spin.r2[r20_key1], 8.33499994313902, 2) 
5285          self.assertAlmostEqual(spin.r2[r20_key2], 8.76118738798082, 2) 
5286          self.assertAlmostEqual(spin.r2[r20_key3], 10.2250821829928, 1) 
5287          self.assertAlmostEqual(spin.pA, 0.950000281516303, 3) 
5288          self.assertAlmostEqual(spin.dw, 4.35845318983581, 2) 
5289          self.assertAlmostEqual(spin.kex/1000, 429.874510184149/1000, 2) 
5290          self.assertAlmostEqual(spin.chi2, 17.3933357984425, 1) 
5291   
5292   
5293 -    def test_korzhnev_2005_15n_zq_data(self): 
5294          """Optimisation of the Korzhnev et al., 2005 15N ZQ CPMG data using the 'NS MMQ 2-site' model. 
5295   
5296          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5297   
5298          Here only the 15N ZQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5299   
5300              - r2 = {'500': 5.909812628572937, '600': 6.663690132557320, '800': 6.787171647689906}, 
5301              - pA = 0.942452612380140, 
5302              - dw = 0.858972784230892, 
5303              - dwH = 0.087155962730608, 
5304              - kex = 373.219151384798920, 
5305              - chi2 = 23.863208106025152. 
5306          """ 
5307   
5308          # Base data setup. 
5309          self.setup_korzhnev_2005_data(data_list=['ZQ']) 
5310   
5311          # Alias the spin. 
5312          spin = return_spin(":9@N") 
5313   
5314          # The R20 keys. 
5315          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5316          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5317          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5318   
5319          # Set the initial parameter values. 
5320          spin.r2 = {r20_key1: 5.91033272691614, r20_key2: 6.66368695342258, r20_key3: 6.78922219135537} 
5321          spin.pA = 0.942457332074014 
5322          spin.dw = 0.850592422908884 
5323          spin.dwH = 0.0881272284455416 
5324          spin.kex = 372.745483351305 
5325   
5326          # Low precision optimisation. 
5327          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5328   
5329          # Monte Carlo simulations. 
5330          self.interpreter.monte_carlo.setup(number=3) 
5331          self.interpreter.monte_carlo.create_data(method='back_calc') 
5332          self.interpreter.monte_carlo.initial_values() 
5333          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5334          self.interpreter.monte_carlo.error_analysis() 
5335   
5336          # Plot the dispersion curves. 
5337          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5338   
5339          # Save the results. 
5340          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5341   
5342          # Printout. 
5343          print("\n\nOptimised parameters:\n") 
5344          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5345          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5346          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5347          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5348          print("%-20s %20.15g" % ("pA", spin.pA)) 
5349          print("%-20s %20.15g" % ("dw", spin.dw)) 
5350          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5351          print("%-20s %20.15g" % ("kex", spin.kex)) 
5352          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5353   
5354          # Checks for residue :9. 
5355          self.assertAlmostEqual(spin.r2[r20_key1], 5.9098385837035, 2) 
5356          self.assertAlmostEqual(spin.r2[r20_key2], 6.66377885876553, 2) 
5357          self.assertAlmostEqual(spin.r2[r20_key3], 6.78717432941353, 2) 
5358          self.assertAlmostEqual(spin.pA, 0.942457141344462, 4) 
5359          self.assertAlmostEqual(spin.dw, 0.84442055695814, 1) 
5360          self.assertAlmostEqual(spin.dwH, 0.0886367674566058, 2) 
5361          self.assertAlmostEqual(spin.kex/1000, 373.243053643367/1000, 3) 
5362          self.assertAlmostEqual(spin.chi2, 23.863211604121, 1) 
5363   
5364   
5365 -    def test_korzhnev_2005_1h_mq_data(self): 
5366          """Optimisation of the Korzhnev et al., 2005 1H MQ CPMG data using the 'NS MMQ 2-site' model. 
5367   
5368          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5369   
5370          Here only the 1H MQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5371   
5372              - r2 = {'500': -0.000016676911302, '600': 0.036594127620440, '800': 2.131014839635728}, 
5373              - pA = 0.936911090448340, 
5374              - dw = 4.325314846914845, 
5375              - dwH = -0.213870168665628, 
5376              - kex = 487.361914835074117, 
5377              - chi2 = 14.870371897291138. 
5378          """ 
5379   
5380          # Base data setup. 
5381          self.setup_korzhnev_2005_data(data_list=['1H MQ']) 
5382   
5383          # Alias the spin. 
5384          spin = return_spin(":9@N") 
5385   
5386          # The R20 keys. 
5387          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5388          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5389          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5390   
5391          # Set the initial parameter values. 
5392          spin.r2 = {r20_key1: 0.000022585022901, r20_key2: 0.039223196112941, r20_key3: 2.136576686700357} 
5393          spin.pA = 0.936884348941701 
5394          spin.dw = 4.326454531583964 
5395          spin.dwH = -0.214026093221782 
5396          spin.kex = 487.043592705469223 
5397   
5398          # Low precision optimisation. 
5399          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=100) 
5400   
5401          # Monte Carlo simulations. 
5402          self.interpreter.monte_carlo.setup(number=3) 
5403          self.interpreter.monte_carlo.create_data(method='back_calc') 
5404          self.interpreter.monte_carlo.initial_values() 
5405          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5406          self.interpreter.monte_carlo.error_analysis() 
5407   
5408          # Plot the dispersion curves. 
5409          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5410   
5411          # Save the results. 
5412          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5413   
5414          # Printout. 
5415          print("\n\nOptimised parameters:\n") 
5416          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5417          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5418          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5419          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5420          print("%-20s %20.15g" % ("pA", spin.pA)) 
5421          print("%-20s %20.15g" % ("dw", spin.dw)) 
5422          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5423          print("%-20s %20.15g" % ("kex", spin.kex)) 
5424          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5425   
5426          # Checks for residue :9. 
5427          self.assertAlmostEqual(spin.r2[r20_key1], 2.48493199969936e-05, 4) 
5428          self.assertAlmostEqual(spin.r2[r20_key2], 0.0382382195911849, 2) 
5429          self.assertAlmostEqual(spin.r2[r20_key3], 2.13397221524655, 2) 
5430          self.assertAlmostEqual(spin.pA, 0.936879359956996, 4) 
5431          self.assertAlmostEqual(spin.dw, 4.32573362253701, 2) 
5432          self.assertAlmostEqual(spin.dwH, -0.213951762275293, 2) 
5433          self.assertAlmostEqual(spin.kex/1000, 487.021196851596/1000, 4) 
5434          self.assertAlmostEqual(spin.chi2, 14.8704048958378, 2) 
5435   
5436   
5437 -    def test_korzhnev_2005_1h_sq_data(self): 
5438          """Optimisation of the Korzhnev et al., 2005 1H SQ CPMG data using the 'NS MMQ 2-site' model. 
5439   
5440          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5441   
5442          Here only the 1H SQ data will be optimised.  The values found by cpmg_fit using just this data are: 
5443   
5444              - r2 = {'500': 6.691697587650816, '600': 6.998915158708793, '800': 5.519267837559072}, 
5445              - pA = 0.946949480545876, 
5446              - dwH = -0.265279672133308, 
5447              - kex = 406.548178869750700, 
5448              - chi2 = 50.400680290545026. 
5449          """ 
5450   
5451          # Base data setup. 
5452          self.setup_korzhnev_2005_data(data_list=['1H SQ']) 
5453   
5454          # Alias the spin. 
5455          spin = return_spin(":9@N") 
5456   
5457          # The R20 keys. 
5458          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5459          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5460          r20_key3 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5461   
5462          # Set the initial parameter values. 
5463          spin.r2 = {r20_key1: 6.69107911078939, r20_key2: 6.99888898689085, r20_key3: 5.52012880268077} 
5464          spin.pA = 0.946990967372467 
5465          spin.dwH = -0.265308128403529 
5466          spin.kex = 406.843250675648 
5467   
5468          # Low precision optimisation. 
5469          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=1000) 
5470   
5471          # Monte Carlo simulations. 
5472          self.interpreter.monte_carlo.setup(number=3) 
5473          self.interpreter.monte_carlo.create_data(method='back_calc') 
5474          self.interpreter.monte_carlo.initial_values() 
5475          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5476          self.interpreter.monte_carlo.error_analysis() 
5477   
5478          # Plot the dispersion curves. 
5479          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5480   
5481          # Save the results. 
5482          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5483   
5484          # Printout. 
5485          print("\n\nOptimised parameters:\n") 
5486          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5487          print("%-20s %20.15g" % ("R2 (500 MHz)", spin.r2[r20_key1])) 
5488          print("%-20s %20.15g" % ("R2 (600 MHz)", spin.r2[r20_key2])) 
5489          print("%-20s %20.15g" % ("R2 (800 MHz)", spin.r2[r20_key3])) 
5490          print("%-20s %20.15g" % ("pA", spin.pA)) 
5491          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5492          print("%-20s %20.15g" % ("kex", spin.kex)) 
5493          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5494   
5495          # Checks for residue :9. 
5496          self.assertAlmostEqual(spin.r2[r20_key1], 6.69168251154302, 2) 
5497          self.assertAlmostEqual(spin.r2[r20_key2], 6.99900388754043, 2) 
5498          self.assertAlmostEqual(spin.r2[r20_key3], 5.51921590064843, 2) 
5499          self.assertAlmostEqual(spin.pA, 0.946951877648819, 4) 
5500          self.assertAlmostEqual(spin.dwH, -0.265280175525516, 3) 
5501          self.assertAlmostEqual(spin.kex/1000, 406.566453278183/1000, 2) 
5502          self.assertAlmostEqual(spin.chi2, 50.4006836222044, 1) 
5503   
5504   
5505 -    def test_korzhnev_2005_all_data(self): 
5506          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5507   
5508          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5509   
5510          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5511   
5512              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5513                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5514                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5515                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5516                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5517                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5518              - pA = 0.943125351763911, 
5519              - dw = 4.421827493809807, 
5520              - dwH = -0.272637034755752, 
5521              - kex = 360.609744568697238, 
5522              - chi2 = 162.589570340050813. 
5523          """ 
5524   
5525          # Base data setup. 
5526          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5527   
5528          # Alias the spin. 
5529          spin = return_spin(":9@N") 
5530   
5531          # The R20 keys. 
5532          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5533          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5534          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5535          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5536          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5537          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5538          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5539          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5540          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5541          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5542          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5543          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5544          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5545          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5546          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5547          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5548          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5549          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5550   
5551          # Set the initial parameter values. 
5552          spin.r2 = { 
5553              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5554              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5555              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5556              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5557              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5558              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5559          } 
5560          spin.pA = 0.943129019477673 
5561          spin.dw = 4.42209952545181 
5562          spin.dwH = -0.27258970590969 
5563          spin.kex = 360.516132791038 
5564   
5565          # Low precision optimisation. 
5566          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-05, max_iter=10) 
5567   
5568          # Monte Carlo simulations. 
5569          self.interpreter.monte_carlo.setup(number=3) 
5570          self.interpreter.monte_carlo.create_data(method='back_calc') 
5571          self.interpreter.monte_carlo.initial_values() 
5572          self.interpreter.minimise.execute(min_algor='simplex', max_iter=10) 
5573          self.interpreter.monte_carlo.error_analysis() 
5574   
5575          # Plot the dispersion curves. 
5576          self.interpreter.relax_disp.plot_disp_curves(dir=ds.tmpdir, force=True) 
5577   
5578          # Save the results. 
5579          self.interpreter.state.save('state', dir=ds.tmpdir, compress_type=1, force=True) 
5580   
5581          # Printout. 
5582          print("\n\nOptimised parameters:\n") 
5583          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5584          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5585          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5586          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5587          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5588          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5589          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5590          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5591          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5592          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5593          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5594          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5595          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5596          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5597          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5598          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5599          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5600          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5601          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5602          print("%-20s %20.15g" % ("pA", spin.pA)) 
5603          print("%-20s %20.15g" % ("dw", spin.dw)) 
5604          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5605          print("%-20s %20.15g" % ("kex", spin.kex)) 
5606          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5607   
5608          # Checks for residue :9. 
5609          self.assertAlmostEqual(spin.r2[r20_key1],  6.67288025927458, 4) 
5610          self.assertAlmostEqual(spin.r2[r20_key2],  6.98951408255098, 4) 
5611          self.assertAlmostEqual(spin.r2[r20_key3],  5.52959273852704, 4) 
5612          self.assertAlmostEqual(spin.r2[r20_key4],  8.39471048876782, 4) 
5613          self.assertAlmostEqual(spin.r2[r20_key5],  8.89290699178799, 4) 
5614          self.assertAlmostEqual(spin.r2[r20_key6],  10.4077068723693, 4) 
5615          self.assertAlmostEqual(spin.r2[r20_key7],  5.93611174376373, 4) 
5616          self.assertAlmostEqual(spin.r2[r20_key8],  6.71735669582514, 4) 
5617          self.assertAlmostEqual(spin.r2[r20_key9],  6.83835225518265, 4) 
5618          self.assertAlmostEqual(spin.r2[r20_key10], 8.59615074668922, 4) 
5619          self.assertAlmostEqual(spin.r2[r20_key11], 10.6512137889291, 4) 
5620          self.assertAlmostEqual(spin.r2[r20_key12], 12.5710822919109, 4) 
5621          self.assertAlmostEqual(spin.r2[r20_key13], 7.85956711501608, 4) 
5622          self.assertAlmostEqual(spin.r2[r20_key14], 8.41891642907918, 4) 
5623          self.assertAlmostEqual(spin.r2[r20_key15], 11.2362089223038, 4) 
5624          self.assertAlmostEqual(spin.r2[r20_key16], 9.1965486378935, 4) 
5625          self.assertAlmostEqual(spin.r2[r20_key17], 9.86031627358462, 4) 
5626          self.assertAlmostEqual(spin.r2[r20_key18], 11.9752375592575, 4) 
5627          self.assertAlmostEqual(spin.pA, 0.943129019477673, 4) 
5628          self.assertAlmostEqual(spin.dw, 4.42209952545181, 4) 
5629          self.assertAlmostEqual(spin.dwH, -0.27258970590969, 4) 
5630          self.assertAlmostEqual(spin.kex/1000, 360.516132791038/1000, 4) 
5631          self.assertAlmostEqual(spin.chi2/1000, 162.596331278669/1000, 3) 
5632   
5633   
5634 -    def test_korzhnev_2005_all_data_disp_speed_bug(self): 
5635          """Optimisation of all the Korzhnev et al., 2005 CPMG data using the 'NS MMQ 2-site' model. 
5636   
5637          This uses the data from Dmitry Korzhnev's paper at U{DOI: 10.1021/ja054550e<http://dx.doi.org/10.1021/ja054550e>}.  This is the 1H SQ, 15N SQ, ZQ, DQ, 1H MQ and 15N MQ data for residue Asp 9 of the Fyn SH3 domain mutant. 
5638   
5639          Here all data will be optimised.  The values found by cpmg_fit using just this data are: 
5640   
5641              - r2 = {'H-S 500':  6.671649051677150, 'H-S 600':  6.988634195648529, 'H-S 800':  5.527971316790596, 
5642                      'N-S 500':  8.394988400015988, 'N-S 600':  8.891359568401835, 'N-S 800': 10.405356669006709, 
5643                      'NHZ 500':  5.936446687394352, 'NHZ 600':  6.717058062814535, 'NHZ 800':  6.838733853403030, 
5644                      'NHD 500':  8.593136215779710, 'NHD 600': 10.651511259239674, 'NHD 800': 12.567902357560627, 
5645                      'HNM 500':  7.851325614877817, 'HNM 600':  8.408803624020202, 'HNM 800': 11.227489645758979, 
5646                      'NHM 500':  9.189159145380575, 'NHM 600':  9.856814478405868, 'NHM 800': 11.967910041807118}, 
5647              - pA = 0.943125351763911, 
5648              - dw = 4.421827493809807, 
5649              - dwH = -0.272637034755752, 
5650              - kex = 360.609744568697238, 
5651              - chi2 = 162.589570340050813. 
5652          """ 
5653   
5654          # Base data setup. 
5655          self.setup_korzhnev_2005_data(data_list=['SQ', '1H SQ', 'DQ', 'ZQ', 'MQ', '1H MQ']) 
5656   
5657          # Alias the spin. 
5658          spin = return_spin(":9@N") 
5659   
5660          # The R20 keys. 
5661          r20_key1  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=500e6) 
5662          r20_key2  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=600e6) 
5663          r20_key3  = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_SQ, frq=800e6) 
5664          r20_key4  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
5665          r20_key5  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=600e6) 
5666          r20_key6  = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
5667          r20_key7  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=500e6) 
5668          r20_key8  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=600e6) 
5669          r20_key9  = generate_r20_key(exp_type=EXP_TYPE_CPMG_ZQ, frq=800e6) 
5670          r20_key10 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=500e6) 
5671          r20_key11 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=600e6) 
5672          r20_key12 = generate_r20_key(exp_type=EXP_TYPE_CPMG_DQ, frq=800e6) 
5673          r20_key13 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=500e6) 
5674          r20_key14 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=600e6) 
5675          r20_key15 = generate_r20_key(exp_type=EXP_TYPE_CPMG_PROTON_MQ, frq=800e6) 
5676          r20_key16 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=500e6) 
5677          r20_key17 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
5678          r20_key18 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
5679   
5680          # Set the initial parameter values. 
5681          spin.r2 = { 
5682              r20_key1:   6.67288025927458, r20_key2:   6.98951408255098, r20_key3:   5.52959273852704, 
5683              r20_key4:   8.39471048876782, r20_key5:   8.89290699178799, r20_key6:  10.40770687236930, 
5684              r20_key7:   5.93611174376373, r20_key8:   6.71735669582514, r20_key9:   6.83835225518265, 
5685              r20_key10:  8.59615074668922, r20_key11: 10.65121378892910, r20_key12: 12.57108229191090, 
5686              r20_key13:  7.85956711501608, r20_key14:  8.41891642907918, r20_key15: 11.23620892230380, 
5687              r20_key16:  9.19654863789350, r20_key17:  9.86031627358462, r20_key18: 11.97523755925750 
5688          } 
5689          spin.pA = 0.943129019477673 
5690          spin.dw = 4.42209952545181 
5691          spin.dwH = -0.27258970590969 
5692          spin.kex = 360.516132791038 
5693   
5694          # Calc the chi2 values at these parameters. 
5695          self.interpreter.minimise.calculate(verbosity=1) 
5696   
5697          # Printout. 
5698          print("\n\nOptimised parameters:\n") 
5699          print("%-20s %-20s" % ("Parameter", "Value (:9)")) 
5700          print("%-20s %20.15g" % ("R2 (1H SQ - 500 MHz)", spin.r2[r20_key1])) 
5701          print("%-20s %20.15g" % ("R2 (1H SQ - 600 MHz)", spin.r2[r20_key2])) 
5702          print("%-20s %20.15g" % ("R2 (1H SQ - 800 MHz)", spin.r2[r20_key3])) 
5703          print("%-20s %20.15g" % ("R2 (SQ - 500 MHz)", spin.r2[r20_key4])) 
5704          print("%-20s %20.15g" % ("R2 (SQ - 600 MHz)", spin.r2[r20_key5])) 
5705          print("%-20s %20.15g" % ("R2 (SQ - 800 MHz)", spin.r2[r20_key6])) 
5706          print("%-20s %20.15g" % ("R2 (ZQ - 500 MHz)", spin.r2[r20_key7])) 
5707          print("%-20s %20.15g" % ("R2 (ZQ - 600 MHz)", spin.r2[r20_key8])) 
5708          print("%-20s %20.15g" % ("R2 (ZQ - 800 MHz)", spin.r2[r20_key9])) 
5709          print("%-20s %20.15g" % ("R2 (DQ - 500 MHz)", spin.r2[r20_key10])) 
5710          print("%-20s %20.15g" % ("R2 (DQ - 600 MHz)", spin.r2[r20_key11])) 
5711          print("%-20s %20.15g" % ("R2 (DQ - 800 MHz)", spin.r2[r20_key12])) 
5712          print("%-20s %20.15g" % ("R2 (1H MQ - 500 MHz)", spin.r2[r20_key13])) 
5713          print("%-20s %20.15g" % ("R2 (1H MQ - 600 MHz)", spin.r2[r20_key14])) 
5714          print("%-20s %20.15g" % ("R2 (1H MQ - 800 MHz)", spin.r2[r20_key15])) 
5715          print("%-20s %20.15g" % ("R2 (MQ - 500 MHz)", spin.r2[r20_key16])) 
5716          print("%-20s %20.15g" % ("R2 (MQ - 600 MHz)", spin.r2[r20_key17])) 
5717          print("%-20s %20.15g" % ("R2 (MQ - 800 MHz)", spin.r2[r20_key18])) 
5718          print("%-20s %20.15g" % ("pA", spin.pA)) 
5719          print("%-20s %20.15g" % ("dw", spin.dw)) 
5720          print("%-20s %20.15g" % ("dwH", spin.dwH)) 
5721          print("%-20s %20.15g" % ("kex", spin.kex)) 
5722          print("%-20s %20.15g\n" % ("chi2", spin.chi2)) 
5723   
5724          # Checks for residue :9. 
5725          self.assertAlmostEqual(spin.chi2/1000, 162.511988511609/1000, 3) 
5726   
5727   
5728 -    def test_kteilum_fmpoulsen_makke_check_graphs(self): 
5729          """Check of all possible dispersion graphs from optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5730   
5731          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5732   
5733          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5734   
5735            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5736            - 0.483 0.89623903 2.4503699912708878 
5737            - 0.545 1.1694838 
5738            - 0.545 1.1761503 
5739            - 0.622 1.294 
5740            - 0.669 1.5176493 
5741            - 0.722 1.6238791 
5742            - 0.813 1.9395758 
5743            - 1.011 2.3558415 10.547000429321157 
5744          """ 
5745   
5746          # Base data setup. 
5747          model = 'TSMFK01' 
5748          expfolder = "acbp_cpmg_disp_048MGuHCl_40C_041223" 
5749          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model=model, expfolder=expfolder) 
5750   
5751          # Alias the spins. 
5752          res61L = cdp.mol[0].res[0].spin[0] 
5753   
5754          # The R20 keys. 
5755          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5756   
5757          # Set the initial parameter values. 
5758          res61L.r2a = {r20_key1: 8.0} 
5759          res61L.dw = 6.5 
5760          res61L.k_AB = 2.5 
5761   
5762          # Low precision optimisation. 
5763          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5764   
5765          # Start testing all possible combinations of graphs. 
5766          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
5767          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
5768          interpolate_types = [INTERPOLATE_DISP] 
5769   
5770          # Write to temp folder. 
5771          result_dir_name = ds.tmpdir 
5772          result_folders = [model] 
5773          spin_id = ":61@N" 
5774   
5775          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
5776          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'KTeilum_FMPoulsen_MAkke_2006'+sep+expfolder+sep+'check_graphs' 
5777   
5778          for result_folder in result_folders: 
5779              for y_axis in y_axis_types: 
5780                  for x_axis in x_axis_types: 
5781                      for interpolate in interpolate_types: 
5782                          # Determine file name: 
5783                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
5784   
5785                          # Make the file name. 
5786                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
5787   
5788                          # Write the curves. 
5789                          dir = result_dir_name+sep+result_folder 
5790                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
5791                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
5792   
5793                          # Get the file path. 
5794                          file_path = get_file_path(file_name, dir) 
5795   
5796                          # Test the plot file exists. 
5797                          print("Testing file access to graph: %s"%file_path) 
5798                          self.assert_(access(file_path, F_OK)) 
5799   
5800                          # Now open, and compare content, line by line. 
5801                          file_prod = open(file_path) 
5802                          lines_prod = file_prod.readlines() 
5803                          file_prod.close() 
5804   
5805                          # Define file to compare against. 
5806                          dir_comp = data_path+sep+result_folder 
5807                          file_path_comp = get_file_path(file_name, dir_comp) 
5808                          file_comp = open(file_path_comp) 
5809                          lines_comp = file_comp.readlines() 
5810                          file_comp.close() 
5811   
5812                          ## Assert number of lines is equal. 
5813                          self.assertEqual(len(lines_prod), len(lines_comp)) 
5814                          for j in range(len(lines_prod)): 
5815                              # Make the string test 
5816                              first_char = lines_prod[j][0] 
5817                              if first_char in ["@", "&"]: 
5818                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
5819                              else: 
5820                                  # Split string in x, y, error. 
5821                                  # The error would change per run. 
5822                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
5823                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
5824                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
5825                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
5826                                  self.assertAlmostEqual(float(y_prod_err), float(y_comp_err)) 
5827   
5828   
5829 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72(self): 
5830          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5831   
5832          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5833          """ 
5834   
5835          # Base data setup. 
5836          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5837   
5838          # Alias the spins. 
5839          res61L = cdp.mol[0].res[0].spin[0] 
5840   
5841          # The R20 keys. 
5842          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5843   
5844          # Set the initial parameter values. 
5845          res61L.r2 = {r20_key1: 8.0} 
5846          res61L.pA = 0.9 
5847          res61L.dw = 6.0 
5848          res61L.kex = 600.0 
5849   
5850          # Low precision optimisation. 
5851          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5852   
5853          # Printout. 
5854          print("\n\nOptimised parameters:\n") 
5855          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5856          print("%-20s %20.15g" % ("R2 (600 MHz)", res61L.r2[r20_key1])) 
5857          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5858          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5859          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5860          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5861   
5862          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5863          self.assertAlmostEqual(res61L.r2[r20_key1], 8.69277980194016, 4) 
5864          self.assertAlmostEqual(res61L.pA, 0.9943781590842946, 5) 
5865          self.assertAlmostEqual(res61L.dw, 6.389453131263374, 3) 
5866          self.assertAlmostEqual(res61L.kex, 609.262167216419, 0) 
5867          self.assertAlmostEqual(res61L.chi2, 65.99987828889657, 5) 
5868   
5869          # Test the conversion to k_AB from kex and pA. 
5870          self.assertEqual(res61L.k_AB, res61L.kex * (1.0 - res61L.pA)) 
5871   
5872          # Test the conversion to k_BA from kex and pA. 
5873          self.assertEqual(res61L.k_BA, res61L.kex * res61L.pA) 
5874   
5875   
5876 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_cr72_full(self): 
5877          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5878   
5879          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5880          """ 
5881   
5882          # Base data setup. 
5883          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='CR72 full', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5884   
5885          # Alias the spins. 
5886          res61L = cdp.mol[0].res[0].spin[0] 
5887   
5888          # The R20 keys. 
5889          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5890   
5891          # Set the initial parameter values. 
5892          res61L.r2a = {r20_key1: 8.0} 
5893          res61L.r2b = {r20_key1: 105.0} 
5894          res61L.pA = 0.9 
5895          res61L.dw = 6.0 
5896          res61L.kex = 500.0 
5897   
5898          # Low precision optimisation. 
5899          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5900   
5901          # Printout. 
5902          print("\n\nOptimised parameters:\n") 
5903          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5904          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5905          print("%-20s %20.15g" % ("R2B (600 MHz)", res61L.r2b[r20_key1])) 
5906          print("%-20s %20.15g" % ("pA", res61L.pA)) 
5907          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5908          print("%-20s %20.15g" % ("kex", res61L.kex)) 
5909          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5910   
5911          # Checks for residue :61. Calculated for 500 Monte Carlo simulations. 
5912          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.044428899438309, 0) 
5913          self.assertAlmostEqual(res61L.r2b[r20_key1], 105.11894506392449, -2) 
5914          self.assertAlmostEqual(res61L.pA, 0.992066883657578, 2) 
5915          self.assertAlmostEqual(res61L.dw, 6.389453586338883, 3) 
5916          self.assertAlmostEqual(res61L.kex, 513.483608742063, -2) 
5917          self.assertAlmostEqual(res61L.chi2, 65.99987828890289, 5) 
5918   
5919   
5920 -    def test_kteilum_fmpoulsen_makke_cpmg_data_048m_guhcl_to_tsmfk01(self): 
5921          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5922   
5923          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 0.48 M GuHCl (guanidine hydrochloride). 
5924   
5925          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl. The precise values are: 
5926   
5927            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5928            - 0.483 0.89623903 2.4503699912708878 
5929            - 0.545 1.1694838 
5930            - 0.545 1.1761503 
5931            - 0.622 1.294 
5932            - 0.669 1.5176493 
5933            - 0.722 1.6238791 
5934            - 0.813 1.9395758 
5935            - 1.011 2.3558415 10.547000429321157 
5936          """ 
5937   
5938          # Base data setup. 
5939          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_048MGuHCl_40C_041223") 
5940   
5941          # Alias the spins. 
5942          res61L = cdp.mol[0].res[0].spin[0] 
5943   
5944          # The R20 keys. 
5945          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086220e6) 
5946   
5947          # Set the initial parameter values. 
5948          res61L.r2a = {r20_key1: 8.0} 
5949          res61L.dw = 6.5 
5950          res61L.k_AB = 2.5 
5951   
5952          # Low precision optimisation. 
5953          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
5954   
5955          # Printout. 
5956          print("\n\nOptimised parameters:\n") 
5957          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
5958          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
5959          print("%-20s %20.15g" % ("dw", res61L.dw)) 
5960          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
5961          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
5962   
5963          # Checks for residue :61. Reference values from paper 
5964   
5965          self.assertAlmostEqual(res61L.k_AB, 2.45, 1) 
5966   
5967   
5968 -    def test_kteilum_fmpoulsen_makke_cpmg_data_101m_guhcl_to_tsmfk01(self): 
5969          """Optimisation of Kaare Teilum, Flemming M Poulsen, Mikael Akke 2006 "acyl-CoA binding protein" CPMG data to the CR72 dispersion model. 
5970   
5971          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0509100103}.  This is CPMG data with a fixed relaxation time period.  Experiment in 1.01 M GuHCl (guanidine hydrochloride). 
5972   
5973          The comparison is to Figure 2, which is for dataset with 1 M GuHCl.  The reported results are expected to be in rad.s^-1.  Conversion into relax stored values is preferably. 
5974   
5975          Representative 15N CPMG relaxation dispersion curve measured on the cross peaks from residue L61 in folded ACBP at pH 5.3, 1 M GuHCl, and 40C: 
5976   
5977            1. The dotted line represents a residue-specific fit of all parameters in Eq. 1: 
5978              - k_AB = 11.3 +/- 0.7 s^-1, 
5979              - dw = (2.45 +/- 0.09) * 10^3 s^-1, 
5980              - R2 = 8.0 +/- 0.5 s^-1. 
5981   
5982            2. The solid line represents a global fit of k_AB to all protein residues and a residue-specific fit of dw and R2.: 
5983              - k_AB = 10.55 +/- 0.08 s^-1, 
5984              - dw = (2.44 +/- 0.08) * 10^3 s^-1, 
5985              - R2 = 8.4 +/- 0.3 s^-1. 
5986   
5987          Conversion of paper results to relax results is performed by: 
5988   
5989            - dw(ppm) = dw(rad.s^-1) * 10^6 * 1/(2*pi) * (gyro1H/(gyro15N*spectrometer_freq)) = 2.45E3 * 1E6 / (2 * math.pi) * (26.7522212E7/(-2.7126E7 * 599.8908622E6)) = -6.41 ppm. 
5990   
5991          Figure 3 shows the ln( k_a [s^-1]) for different concentrations of GuHCl.  The precise values are: 
5992   
5993            - [GuHCL][M] ln(k_a[s^-1]) k_a[s^-1] 
5994            - 0.483 0.89623903 2.4503699912708878 
5995            - 0.545 1.1694838 
5996            - 0.545 1.1761503 
5997            - 0.622 1.294 
5998            - 0.669 1.5176493 
5999            - 0.722 1.6238791 
6000            - 0.813 1.9395758 
6001            - 1.011 2.3558415 10.547000429321157 
6002          """ 
6003   
6004          # Base data setup. 
6005          self.setup_kteilum_fmpoulsen_makke_cpmg_data(model='TSMFK01', expfolder="acbp_cpmg_disp_101MGuHCl_40C_041223") 
6006   
6007          # Alias the spins. 
6008          res61L = cdp.mol[0].res[0].spin[0] 
6009   
6010          # The R20 keys. 
6011          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.89086270e6) 
6012   
6013          # Set the initial parameter values. 
6014          res61L.r2a = {r20_key1: 8.0} 
6015          res61L.dw = 6.5 
6016          res61L.k_AB = 11.0 
6017   
6018          # Low precision optimisation. 
6019          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
6020   
6021          # Printout. 
6022          print("\n\nOptimised parameters:\n") 
6023          print("%-20s %-20s" % ("Parameter", "Value (:61)")) 
6024          print("%-20s %20.15g" % ("R2A (600 MHz)", res61L.r2a[r20_key1])) 
6025          print("%-20s %20.15g" % ("dw", res61L.dw)) 
6026          print("%-20s %20.15g" % ("k_AB", res61L.k_AB)) 
6027          print("%-20s %20.15g\n" % ("chi2", res61L.chi2)) 
6028   
6029          # Checks for residue :61. Reference values from paper 
6030   
6031          self.assertAlmostEqual(res61L.r2a[r20_key1], 8.4, 0) 
6032          self.assertAlmostEqual(res61L.dw, 6.41, 0) 
6033          self.assertAlmostEqual(res61L.k_AB, 10.55, 0) 
6034   
6035   
6036 -    def test_lm63_3site_synthetic(self): 
6037          """Test the 'LM63 3-site' dispersion model using the pure noise-free synthetic data.""" 
6038   
6039          # The path to the data files. 
6040          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'lm63_3site' 
6041   
6042          # Load the state file. 
6043          self.interpreter.reset() 
6044          self.interpreter.state.load(data_path+sep+'r2eff_values') 
6045   
6046          # A new data pipe. 
6047          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to='LM63 3-site', bundle_to='relax_disp') 
6048          self.interpreter.pipe.switch(pipe_name='LM63 3-site') 
6049   
6050          # Set up the model data. 
6051          self.interpreter.relax_disp.select_model(model='LM63 3-site') 
6052          self.interpreter.value.copy(pipe_from='R2eff - relax_disp', pipe_to='LM63 3-site', param='r2eff') 
6053          self.interpreter.spin.isotope('15N') 
6054   
6055          # Alias the spins. 
6056          spin1 = return_spin(":1") 
6057          spin2 = return_spin(":2") 
6058   
6059          # The R20 keys. 
6060          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=500e6) 
6061          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=800e6) 
6062   
6063          # Manually set the parameter values. 
6064          spin1.r2 = {r20_key1: 12.0, r20_key2: 12.0} 
6065          spin1.phi_ex_B = 0.1 
6066          spin1.phi_ex_C = 0.5 
6067          spin1.kB = 1500.0 
6068          spin1.kC = 2500.0 
6069          spin2.r2 = {r20_key1: 15.0, r20_key2: 15.0} 
6070          spin2.phi_ex_B = 0.1 
6071          spin2.phi_ex_C = 0.5 
6072          spin2.kB = 1500.0 
6073          spin2.kC = 2500.0 
6074   
6075          # Low precision optimisation. 
6076          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-05, grad_tol=None, max_iter=1000, constraints=True, scaling=True, verbosity=1) 
6077   
6078          # Monte Carlo simulations. 
6079          self.interpreter.monte_carlo.setup(number=3) 
6080          self.interpreter.monte_carlo.create_data(method='back_calc') 
6081          self.interpreter.monte_carlo.initial_values() 
6082          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-2, grad_tol=None, max_iter=10, constraints=True, scaling=True, verbosity=1) 
6083          self.interpreter.monte_carlo.error_analysis() 
6084   
6085          # Save the results. 
6086          self.interpreter.results.write(file='devnull', compress_type=1, force=True) 
6087   
6088          # The model checks. 
6089          print("\n\nOptimised parameters:\n") 
6090          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
6091          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
6092          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
6093          print("%-20s %20.15g %20.15g" % ("phi_ex_B", spin1.phi_ex_B, spin2.phi_ex_B)) 
6094          print("%-20s %20.15g %20.15g" % ("phi_ex_C", spin1.phi_ex_C, spin2.phi_ex_C)) 
6095          print("%-20s %20.15g %20.15g" % ("kB", spin1.kB, spin2.kB)) 
6096          print("%-20s %20.15g %20.15g" % ("kC", spin1.kC, spin2.kC)) 
6097          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
6098          self.assertAlmostEqual(spin1.r2[r20_key1], 12.0, 2) 
6099          self.assertAlmostEqual(spin1.r2[r20_key2], 12.0, 2) 
6100          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
6101          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
6102          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
6103          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
6104          self.assertAlmostEqual(spin1.chi2, 0.0, 3) 
6105          self.assertAlmostEqual(spin2.r2[r20_key1], 15.0, 3) 
6106          self.assertAlmostEqual(spin2.r2[r20_key2], 15.0, 3) 
6107          self.assertAlmostEqual(spin1.phi_ex_B, 0.1, 3) 
6108          self.assertAlmostEqual(spin1.phi_ex_C, 0.5, 3) 
6109          self.assertAlmostEqual(spin1.kB/1000, 1500.0/1000, 3) 
6110          self.assertAlmostEqual(spin1.kC/1000, 2500.0/1000, 3) 
6111          self.assertAlmostEqual(spin2.chi2, 0.0, 3) 
6112   
6113   
6114 -    def test_m61_data_to_m61(self): 
6115          """Test the relaxation dispersion 'M61' model curve fitting to fixed time synthetic data.""" 
6116   
6117          # Fixed time variable. 
6118          ds.fixed = True 
6119   
6120          # Execute the script. 
6121          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6122   
6123          # The original parameters. 
6124          i0 = [100000.0, 20000.0] 
6125          r1rho_prime = [2.25, 24.0] 
6126          pA = 0.7 
6127          kex = 1000.0 
6128          delta_omega = [1.0, 2.0] 
6129          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6130          phi_ex = [] 
6131          for i in range(2): 
6132              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6133          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6134   
6135          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6136          self.interpreter.pipe.switch('R2eff - relax_disp') 
6137          spin_index = 0 
6138          for spin, spin_id in spin_loop(return_id=True): 
6139              # Printout. 
6140              print("\nSpin %s." % spin_id) 
6141   
6142              # Check the fitted parameters. 
6143              for i in range(len(keys)): 
6144                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6145   
6146              # Increment the spin index. 
6147              spin_index += 1 
6148   
6149          # The R20 keys. 
6150          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6151   
6152          # Switch to the 'M61' model data pipe, then check for each spin. 
6153          self.interpreter.pipe.switch('M61 - relax_disp') 
6154          spin_index = 0 
6155          for spin, spin_id in spin_loop(return_id=True): 
6156              # Printout. 
6157              print("\nSpin %s." % spin_id) 
6158   
6159              # Check the fitted parameters. 
6160              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6161              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6162              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6163   
6164              # Increment the spin index. 
6165              spin_index += 1 
6166   
6167   
6168 -    def test_m61_exp_data_to_m61(self): 
6169          """Test the relaxation dispersion 'M61' model curve fitting to the full exponential synthetic data.""" 
6170   
6171          # Fixed time variable. 
6172          ds.fixed = False 
6173   
6174          # Single spin optimisation. 
6175          ds.single = True 
6176   
6177          # Execute the script. 
6178          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61.py') 
6179   
6180          # The original parameters. 
6181          i0 = [100000.0, 20000.0] 
6182          r1rho_prime = [2.25, 24.0] 
6183          pA = 0.7 
6184          kex = 1000.0 
6185          delta_omega = [1.0, 2.0] 
6186          keys = ['r1rho_800.00000000_0.000_1000.000', 'r1rho_800.00000000_0.000_1500.000', 'r1rho_800.00000000_0.000_2000.000', 'r1rho_800.00000000_0.000_2500.000', 'r1rho_800.00000000_0.000_3000.000', 'r1rho_800.00000000_0.000_3500.000', 'r1rho_800.00000000_0.000_4000.000', 'r1rho_800.00000000_0.000_4500.000', 'r1rho_800.00000000_0.000_5000.000', 'r1rho_800.00000000_0.000_5500.000', 'r1rho_800.00000000_0.000_6000.000'] 
6187          phi_ex = [] 
6188          for i in range(2): 
6189              phi_ex.append(pA * (1.0 - pA) * delta_omega[i]**2) 
6190          rates = [[3.59768160399, 2.85730469783, 2.59328084312, 2.47019857325, 2.40310451058, 2.36256876552, 2.33622716364, 2.31815271355, 2.30521680479, 2.29564174079, 2.28835686631], [29.390726416, 26.4292187913, 25.3731233725, 24.880794293, 24.6124180423, 24.4502750621, 24.3449086546, 24.2726108542, 24.2208672192, 24.1825669632, 24.1534274652]] 
6191   
6192          # Switch to the 'R2eff' model data pipe, then check for each spin. 
6193          self.interpreter.pipe.switch('R2eff - relax_disp') 
6194          spin_index = 0 
6195          for spin, spin_id in spin_loop(return_id=True): 
6196              # Printout. 
6197              print("\nSpin %s." % spin_id) 
6198   
6199              # Check the fitted parameters. 
6200              for i in range(len(keys)): 
6201                  self.assertAlmostEqual(spin.r2eff[keys[i]]/10.0, rates[spin_index][i]/10.0, 2) 
6202   
6203              # Increment the spin index. 
6204              spin_index += 1 
6205   
6206          # The R20 keys. 
6207          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6208   
6209          # Switch to the 'M61' model data pipe, then check for each spin. 
6210          self.interpreter.pipe.switch('M61 - relax_disp') 
6211          spin_index = 0 
6212          for spin, spin_id in spin_loop(return_id=True): 
6213              # Printout. 
6214              print("\nSpin %s." % spin_id) 
6215   
6216              # Check the fitted parameters. 
6217              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6218              self.assertAlmostEqual(spin.phi_ex, phi_ex[spin_index], 2) 
6219              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6220   
6221              # Increment the spin index. 
6222              spin_index += 1 
6223   
6224   
6225 -    def test_m61b_data_to_m61b(self): 
6226          """Test the relaxation dispersion 'M61 skew' model curve fitting to fixed time synthetic data.""" 
6227   
6228          # Execute the script. 
6229          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_on_res_m61b.py') 
6230   
6231          # The original parameters. 
6232          i0 = [100000.0, 20000.0] 
6233          r1rho_prime = [10.0, 24.0] 
6234          pA = 0.95 
6235          kex = 2000.0 
6236          delta_omega = [1.0, 2.0] 
6237   
6238          # The R20 keys. 
6239          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
6240   
6241          # Switch to the 'M61 skew' model data pipe, then check for each spin. 
6242          self.interpreter.pipe.switch("%s - relax_disp" % MODEL_M61B) 
6243          spin_index = 0 
6244          for spin, spin_id in spin_loop(return_id=True): 
6245              # Printout. 
6246              print("\nSpin %s." % spin_id) 
6247   
6248              # Check the fitted parameters. 
6249              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index]/10, 2) 
6250              self.assertAlmostEqual(spin.pA, pA, 2) 
6251              self.assertAlmostEqual(spin.dw, dw[spin_index], 2) 
6252              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 2) 
6253   
6254              # Increment the spin index. 
6255              spin_index += 1 
6256   
6257   
6258 -    def test_model_nesting_and_param(self): 
6259          """Test that all models which can nest, have all their parameters converted.""" 
6260   
6261          # Set the experiment type. 
6262          cdp.exp_type_list = EXP_TYPE_LIST 
6263   
6264          # Get info for all models. 
6265          all_models_info = models_info(models=MODEL_LIST_FULL) 
6266   
6267          # Loop over all models. 
6268          print("Printing the listed of nested models for each model.") 
6269          print("#########################################") 
6270          for model_info in all_models_info: 
6271              print("%s"%model_info.model), 
6272              print("<-"), 
6273              nest_list = model_info.nest_list 
6274              if nest_list == None: 
6275                  nest_list = ["None"] 
6276              print(', '.join(map(str, nest_list))) 
6277   
6278              # Skip if there is no model to nest from. 
6279              if nest_list == ["None"]: 
6280                  continue 
6281   
6282              # Assign params to variable. 
6283              model_params = model_info.params 
6284   
6285              # Now loop over the nested models. 
6286              for nested_model in nest_list: 
6287                  # Get the params for the nested model. 
6288                  nested_model_params = MODEL_PARAMS[nested_model] 
6289   
6290                  # Get the dictionary of parameter conversion. 
6291                  par_dic = nesting_param(model_params=model_params, nested_model_params=nested_model_params) 
6292   
6293                  # Test the number of elements in the dictionary. 
6294                  self.assertEqual(len(par_dic), len(model_params)) 
6295   
6296                  # Loop over dictionary. 
6297                  for param in par_dic: 
6298                          if param != par_dic[param]: 
6299                              print("Model:'%s', Nested model:'%s', Copying '%s' to '%s'." % (model_info.model, nested_model, par_dic[param], param)) 
6300                          self.assertNotEqual(par_dic[param], None) 
6301   
6302   
6303 -    def test_ns_mmq_3site(self): 
6304          """Compare the 'NS MMQ 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6305   
6306          # Execute the script. 
6307          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site.py') 
6308   
6309          # Check the chi-squared value. 
6310          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6311   
6312   
6313 -    def test_ns_mmq_3site_linear(self): 
6314          """Compare the 'NS MMQ 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6315   
6316          # Execute the script. 
6317          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_mmq_3site_linear.py') 
6318   
6319          # Check the chi-squared value. 
6320          self.assertAlmostEqual(cdp.mol[0].res[0].spin[1].chi2, 0.0, 3) 
6321   
6322   
6323 -    def test_ns_r1rho_3site(self): 
6324          """Compare the 'NS R1rho 3-site' dispersion model to synthetic data from cpmg_fit.""" 
6325   
6326          # Execute the script. 
6327          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site.py') 
6328   
6329          # Check the chi-squared value. 
6330          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 136.13141468674999, 3) 
6331   
6332   
6333 -    def test_ns_r1rho_3site_linear(self): 
6334          """Compare the 'NS R1rho 3-site linear' dispersion model to synthetic data from cpmg_fit.""" 
6335   
6336          # Execute the script. 
6337          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'ns_r1rho_3site_linear.py') 
6338   
6339          # Check the chi-squared value. 
6340          self.assertAlmostEqual(cdp.mol[0].res[0].spin[0].chi2, 0.030959849811015544, 3) 
6341   
6342   
6343 -    def test_paul_schanda_nov_2015(self): 
6344          """This test truncated private data which was provided by Paul Schanda.  This systemtest uncovers some unfortunate problems when 
6345          running an analysis and reading points by the R2eff method. 
6346          """ 
6347   
6348          # Assign 
6349          outdir = ds.tmpdir 
6350   
6351          # Execute the setup and creation of files. 
6352          self.setup_paul_schanda_nov_2015(outdir=outdir) 
6353   
6354          # Minimum: Just read the sequence data, but this misses a lot of information. 
6355          self.interpreter.sequence.read(file='residues.txt', res_num_col=1, dir=outdir) 
6356   
6357          # Open the settings file. 
6358          set_file = open(outdir+sep+"exp_settings.txt") 
6359          set_file_lines = set_file.readlines() 
6360   
6361          # Now load the data. 
6362          for line in set_file_lines: 
6363              if "#" in line[0]: 
6364                  continue 
6365   
6366              # Get data 
6367              field, RF_field_strength_kHz, f_name = line.split() 
6368   
6369              # Assign data 
6370              spec_id = f_name 
6371              self.interpreter.relax_disp.exp_type(spectrum_id=spec_id, exp_type='R1rho') 
6372   
6373              # Set the spectrometer frequency 
6374              self.interpreter.spectrometer.frequency(id=spec_id, frq=float(field), units='MHz') 
6375   
6376              # Is in kHz, som convert to Hz 
6377              disp_frq = float(RF_field_strength_kHz)*1000 
6378   
6379              # Set The spin-lock field strength, nu1, in Hz 
6380              self.interpreter.relax_disp.spin_lock_field(spectrum_id=spec_id, field=disp_frq) 
6381   
6382              # Read the R2eff data 
6383              self.interpreter.relax_disp.r2eff_read(id=spec_id, file=f_name, dir=None, disp_frq=disp_frq, res_num_col=1, data_col=2, error_col=3) 
6384   
6385              # Is this necessary? The time, in seconds, of the relaxation period. 
6386              #self.interpreter.relax_disp.relax_time(spectrum_id=spec_id, time=time_sl) 
6387   
6388   
6389          # Check that the number of R2eff points is correct after dropping 1 datapoint for spin 51. 
6390          r2eff_points = [] 
6391          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
6392              # Loop over the R2eff points 
6393              for key in cur_spin.r2eff: 
6394                  value = cur_spin.r2eff[key] 
6395                  err = cur_spin.r2eff_err[key] 
6396                  r2eff_points.append(value) 
6397   
6398                  # Test that values and errors are not nan. 
6399                  self.assert_(not isnan(value)) 
6400                  self.assert_(not isnan(err)) 
6401   
6402   
6403          # Test the number of r2eff points. One is subtracted, due to one of the error values are "nan" in spin 51. 
6404          self.assertEqual(len(r2eff_points), 2*(10+19)-1) 
6405   
6406          # Test stored value in the pipe. 
6407          self.assertEqual(len(cdp.mol), 1) 
6408          self.assertEqual(cdp.mol[0].name, None) 
6409          self.assertEqual(len(cdp.mol[0].res), 2) 
6410   
6411          self.assertEqual(cdp.spectrometer_frq_count, 2) 
6412          print cdp.spectrometer_frq_list 
6413          self.assertEqual(cdp.spectrometer_frq_list, [600000000.0, 950000000.0]) 
6414          self.assertEqual(cdp.exp_type_list, ['R1rho']) 
6415   
6416          # Test the number of frequencies. 
6417          count_600 = 0 
6418          count_950 = 0 
6419          for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
6420              if frq == cdp.spectrometer_frq_list[0]: 
6421                  count_600 += 1 
6422              elif frq == cdp.spectrometer_frq_list[1]: 
6423                  count_950 += 1 
6424   
6425          # Assert the number of points 
6426          self.assertEqual(count_600, 10) 
6427          self.assertEqual(count_950, 19) 
6428   
6429          # Name the isotope for field strength scaling. 
6430          self.interpreter.spin.isotope(isotope='15N') 
6431   
6432          # Now test that the plotting can be performed of just the raw data. 
6433          self.assertRaises(RelaxError, self.interpreter.relax_disp.plot_disp_curves, dir=outdir, y_axis='r2_eff', x_axis='disp', num_points=1000, extend_hz=500.0, extend_ppm=500.0, interpolate='disp', force=True) 
6434          self.interpreter.relax_disp.select_model(model=MODEL_R2EFF) 
6435          self.interpreter.relax_disp.plot_disp_curves(dir=outdir, y_axis='r2_eff', x_axis='disp', num_points=1000, extend_hz=500.0, extend_ppm=500.0, interpolate='disp', force=True) 
6436   
6437   
6438          # Number of grid search increments.  If set to None, then the grid search will be turned off and the default parameter values will be used instead. 
6439          #GRID_INC = None 
6440          GRID_INC = 21 
6441          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
6442          MC_NUM = 3 
6443          # Model selection technique. 
6444          MODSEL = 'AIC' 
6445          # Which models to analyse ? 
6446          MODELS = [MODEL_NOREX, MODEL_M61] 
6447          # Fit, instead of read. Off for On-resonance. 
6448          r1_fit = False 
6449          # Set the initial guess from the minimum R2eff point 
6450          set_grid_r20=True 
6451   
6452          # Execute the auto-analysis (fast). 
6453          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
6454          OPT_FUNC_TOL = 1e-1 
6455          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
6456          OPT_MAX_ITERATIONS = 1000 
6457          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
6458   
6459          # Go 
6460          relax_disp.Relax_disp(pipe_name="relax_disp", pipe_bundle="relax_disp", results_dir=outdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=None, modsel=MODSEL,  pre_run_dir=None, optimise_r2eff=False, insignificance=0.0, numeric_only=False, mc_sim_all_models=False, eliminate=True, set_grid_r20=set_grid_r20, r1_fit=r1_fit) 
6461   
6462          # Now simulate that all spins are first deselected, and then selected. 
6463          self.interpreter.deselect.all() 
6464          sel_ids = [ 
6465          ":12", 
6466          ":51", 
6467          ] 
6468          for sel_spin in sel_ids: 
6469              print("Selecting spin %s"%sel_spin) 
6470              self.interpreter.select.spin(spin_id=sel_spin, change_all=False) 
6471   
6472          # Inspect which residues should be analysed together for a clustered/global fit. 
6473          cluster_ids = sel_ids 
6474   
6475          # Cluster spins 
6476          for curspin in cluster_ids: 
6477              print("Adding spin %s to cluster"%curspin) 
6478              self.interpreter.relax_disp.cluster('model_cluster', curspin) 
6479   
6480          # Show the pipe 
6481          print("\nPrinting all the available pipes.") 
6482          self.interpreter.pipe.display() 
6483   
6484          # Get the selected models 
6485          print("\nChecking which model is stored per spin.") 
6486          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6487              print("For spin_id '%s the model is '%s''"%(spin_id, curspin.model)) 
6488   
6489          # Copy pipe and switch to it. 
6490          self.interpreter.pipe.copy(pipe_from="final - relax_disp", pipe_to="relax_disp_cluster", bundle_to="relax_disp_cluster") 
6491          self.interpreter.pipe.switch(pipe_name="relax_disp_cluster") 
6492          self.interpreter.pipe.display() 
6493   
6494          # Go again with clustered spins. 
6495          relax_disp.Relax_disp(pipe_name="relax_disp_cluster", pipe_bundle="relax_disp_cluster", results_dir=outdir+sep+"cluster", models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, exp_mc_sim_num=None, modsel=MODSEL,  pre_run_dir=None, optimise_r2eff=False, insignificance=0.0, numeric_only=False, mc_sim_all_models=False, eliminate=True, set_grid_r20=set_grid_r20, r1_fit=r1_fit) 
6496   
6497          # Get the clustered fitted values 
6498          print("\nChecking which value is stored per spin.") 
6499          kex = None 
6500          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
6501              if kex == None: 
6502                  kex = curspin.kex 
6503              self.assertEqual(curspin.kex, kex) 
6504              print("For spin_id %s the kex is %.3f"%(spin_id, kex)) 
6505   
6506   
6507 -    def test_repeat_cpmg(self): 
6508          """Test the protocol for repeated dispersion analysis. The class: relax_disp_repeat_cpmg. 
6509   
6510          U{task #7826<https://gna.org/task/index.php?7826>}. Write an python class for the repeated analysis of dispersion data. 
6511          """ 
6512   
6513          # Reset. 
6514          self.interpreter.reset() 
6515   
6516          # Define base path to files. 
6517          base_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1' 
6518   
6519          # Setup dictionary with settings. 
6520          sdic = {} 
6521   
6522          # Spectrometer frqs in list. 
6523          sfrq_1 = 499.86214 
6524          sfrq_2 = 599.8908587 
6525          sfrqs = [sfrq_1, sfrq_2] 
6526   
6527          # Store in dictionary. 
6528          sdic['sfrqs'] = sfrqs 
6529   
6530          # Store unit for frq. 
6531          sdic['sfrq_unit'] = 'MHz' 
6532   
6533          # Store exp_type 
6534          sdic['exp_type'] = 'SQ CPMG' 
6535   
6536          # Store spin isotope 
6537          sdic['isotope'] = '15N' 
6538   
6539          # How intensity was measured. 
6540          sdic['int_method'] = 'height' 
6541   
6542          # Define the time for result directory. 
6543          sdic['time'] = '2014_09' 
6544   
6545          # Initialize frq dics. 
6546          for frq in sfrqs: 
6547              key = DIC_KEY_FORMAT % (frq) 
6548              sdic[key] = {} 
6549   
6550          # Set keys. 
6551          e_1 = DIC_KEY_FORMAT % (sfrq_1) 
6552          e_2 = DIC_KEY_FORMAT % (sfrq_2) 
6553   
6554          # Store time T2. 
6555          sdic[e_1]['time_T2'] = 0.04 
6556          sdic[e_2]['time_T2'] = 0.06 
6557   
6558          # Set ncyc. 
6559          ncyc_1 = array([20, 0, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28, 0]) 
6560          ncyc_2 = array([28, 0, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 0, 24, 14, 22]) 
6561   
6562          # Calculate the cpmg_frq and store. 
6563          sdic[e_1]['cpmg_frqs'] = ncyc_1 / sdic[e_1]['time_T2'] 
6564          sdic[e_2]['cpmg_frqs'] = ncyc_2 / sdic[e_2]['time_T2'] 
6565   
6566          # Define peak lists. 
6567          peaks_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files' 
6568          peaks_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'analysis_FT' +sep+ 'ser_files'  
6569          sdic[e_1]['peaks_folder'] = peaks_folder_1 
6570          sdic[e_2]['peaks_folder'] = peaks_folder_2 
6571   
6572          # Define folder to all rmsd files. 
6573          rmsd_folder_1 = base_path +sep+ 'cpmg_disp_sod1d90a_060518' +sep+ 'cpmg_disp_sod1d90a_060518_normal.fid' +sep+ 'ft2_data' 
6574          rmsd_folder_2 = base_path +sep+ 'cpmg_disp_sod1d90a_060521' +sep+ 'cpmg_disp_sod1d90a_060521_normal.fid' +sep+ 'ft2_data' 
6575          sdic[e_1]['rmsd_folder'] = rmsd_folder_1  
6576          sdic[e_2]['rmsd_folder'] = rmsd_folder_2 
6577   
6578          # Define temporary folder. 
6579          sdic['results_dir'] = self.tmpdir 
6580   
6581          # Setup class with data. 
6582          RDR =  Relax_disp_rep(sdic) 
6583   
6584          # Setup base information. 
6585          RDR.set_base_cpmg(method='FT', glob_ini=128) 
6586   
6587          methods = ['FT', 'MDD'] 
6588          #methods = ['FT'] 
6589   
6590          # Set the intensity. 
6591          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=False, set_rep=True) 
6592          #RDR.set_int(methods=methods, list_glob_ini=[128, 126], set_rmsd=True, set_rep=False) 
6593   
6594          # Try plot some intensity correlations. 
6595          if True: 
6596              selection = None 
6597   
6598              # Now make a spin selection. 
6599              int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128, 126], selection=selection) 
6600   
6601              # For mdd 
6602              int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6603   
6604              # Plot correlation of intensity 
6605              fig1 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6606              fig2 = [[int_ft_sel, int_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6607              corr_data = [fig1, fig2] 
6608   
6609              write_stats = True 
6610              RDR.plot_int_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6611   
6612              # Open stat file. 
6613              if write_stats: 
6614                  for i, corr_data_i in enumerate(corr_data): 
6615                      data, methods, glob_inis = corr_data[i] 
6616                      data_x, data_y = data 
6617                      method_x, method_y = methods 
6618                      glob_ini_x, glob_ini_y = glob_inis 
6619                      x = data_x[str(glob_ini_x)]['peak_intensity_arr'] 
6620                      np = len(x) 
6621   
6622                      file_name_ini = 'int_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6623   
6624                      if selection == None: 
6625                          file_name = file_name_ini + '_all.txt' 
6626                      else: 
6627                          file_name = file_name_ini + '_sel.txt' 
6628                      path = RDR.results_dir 
6629                      data = extract_data(file=file_name, dir=path) 
6630   
6631                      # Loop over the lines. 
6632                      for i, data_i in enumerate(data): 
6633                          print(i, data_i) 
6634   
6635   
6636          # Try plot some intensity statistics. 
6637          if True: 
6638              # Collect r2eff values. 
6639              selections = [None, ':2,3'] 
6640              for selection in selections: 
6641                  int_ft_sel = RDR.col_int(method='FT', list_glob_ini=[128], selection=selection) 
6642                  int_mdd_sel = RDR.col_int(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6643   
6644                  # Get R2eff stats. 
6645                  int_stat_dic = RDR.get_int_stat_dic(list_int_dics=[int_ft_sel, int_mdd_sel], list_glob_ini=[128, 126]) 
6646   
6647                  ## Plot R2eff stats 
6648                  write_stats = True 
6649                  RDR.plot_int_stat(int_stat_dic=int_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126], show=False, write_stats=write_stats) 
6650   
6651                  # Open stat file. 
6652                  if write_stats: 
6653                      if selection == None: 
6654                          file_name = 'int_stat_all.txt' 
6655                      else: 
6656                          file_name = 'int_stat_sel.txt' 
6657                      path = RDR.results_dir 
6658                      data = extract_data(file=file_name, dir=path) 
6659   
6660                      # Loop over the lines. 
6661                      for i, data_i in enumerate(data): 
6662                          print(i, data_i) 
6663   
6664   
6665          # Try write some R2eff correlations. 
6666          if True: 
6667              selection = None 
6668              # Collect r2eff values. 
6669              r2eff_ft_all = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6670   
6671              # For all spins, mdd 
6672              r2eff_mdd_all = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6673   
6674              # Plot correlation of intensity 
6675              fig1 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 128]] 
6676              fig2 = [[r2eff_ft_all, r2eff_mdd_all], ['FT', 'MDD'], [128, 126]] 
6677              corr_data = [fig1, fig2] 
6678   
6679              write_stats = True 
6680              RDR.plot_r2eff_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6681   
6682              # Open stat file. 
6683              if write_stats: 
6684                  for i, corr_data_i in enumerate(corr_data): 
6685                      data, methods, glob_inis = corr_data[i] 
6686                      data_x, data_y = data 
6687                      method_x, method_y = methods 
6688                      glob_ini_x, glob_ini_y = glob_inis 
6689                      x = data_x[str(glob_ini_x)]['r2eff_arr'] 
6690                      np = len(x) 
6691   
6692                      file_name_ini = 'r2eff_corr_%s_%s_%s_%s_NP_%i' % (method_x, glob_ini_x, method_y, glob_ini_y, np) 
6693   
6694                      if selection == None: 
6695                          file_name = file_name_ini + '_all.txt' 
6696                      else: 
6697                          file_name = file_name_ini + '_sel.txt' 
6698                      path = RDR.results_dir 
6699                      data = extract_data(file=file_name, dir=path) 
6700   
6701                      # Loop over the lines. 
6702                      for i, data_i in enumerate(data): 
6703                          print(i, data_i) 
6704   
6705   
6706          # Try plot some R2eff statistics. 
6707          if True: 
6708              # Collect r2eff values. 
6709              selections = [None, ':2,3'] 
6710              for selection in selections: 
6711                  r2eff_ft_sel = RDR.col_r2eff(method='FT', list_glob_ini=[128, 126, 6], selection=selection) 
6712                  r2eff_mdd_sel = RDR.col_r2eff(method='MDD', list_glob_ini=[128, 126], selection=selection) 
6713   
6714                  # Get R2eff stats. 
6715                  r2eff_stat_dic = RDR.get_r2eff_stat_dic(list_r2eff_dics=[r2eff_ft_sel, r2eff_mdd_sel], list_glob_ini=[128, 126]) 
6716   
6717                  ## Plot R2eff stats 
6718                  write_stats = True 
6719                  RDR.plot_r2eff_stat(r2eff_stat_dic=r2eff_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6720   
6721                  # Open stat file. 
6722                  if write_stats: 
6723                      if selection == None: 
6724                          file_name = 'r2eff_stat_all.txt' 
6725                      else: 
6726                          file_name = 'r2eff_stat_sel.txt' 
6727                      path = RDR.results_dir 
6728                      data = extract_data(file=file_name, dir=path) 
6729   
6730                      # Loop over the lines. 
6731                      for i, data_i in enumerate(data): 
6732                          print(i, data_i) 
6733   
6734   
6735          # Do minimisation individual. 
6736          if True: 
6737              methods = ['FT', 'MDD'] 
6738              # Now calculate R2eff. 
6739              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6740   
6741              min_methods = [['FT'], ['MDD']] 
6742              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6743   
6744              #min_methods = [['FT']] 
6745              #min_list_glob_ini = [[128]] 
6746              #selection = ':2,3' 
6747              selection = None 
6748   
6749              for i, methods in enumerate(min_methods): 
6750                  list_glob_ini = min_list_glob_ini[i] 
6751   
6752                  if True: 
6753                      # First get data. 
6754                      if True: 
6755                          # First load all data. 
6756                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6757   
6758                      # Then set R20 
6759                      if True: 
6760                          # Set R20 from min R2eff in preparation for Grid search. 
6761                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, model_from=MODEL_R2EFF, analysis='grid_setup_ind', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6762   
6763                      # Check and print parameters. 
6764                      if True: 
6765                          # Print for pipe name 
6766                          method = methods[0] 
6767                          glob_ini = list_glob_ini[0] 
6768   
6769                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup_ind', glob_ini=glob_ini) 
6770                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6771   
6772                      # Then Grid search. 
6773                      if True: 
6774                          # Do Grid search. 
6775                          RDR.minimise_grid_search(inc=4, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6776   
6777                  # Then Minimise. 
6778                  if True: 
6779                      # Minimise 
6780                      RDR.opt_max_iterations = int(1e2) 
6781                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min_ind', analysis_from='grid_setup_ind', list_glob_ini=list_glob_ini, force=True) 
6782   
6783                  #print asd 
6784   
6785          # Plot statistics. 
6786          # Try plot some minimisation correlations. 
6787          if True: 
6788              selections = [None, ':2,3'] 
6789              for selection in selections: 
6790                  # Collect param values. 
6791                  analysis = 'min_ind' 
6792                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6793                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6794   
6795                  fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6796                  fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6797                  corr_data = [fig1, fig2] 
6798   
6799                  write_stats = True 
6800                  RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6801   
6802                  # Open stat file. 
6803                  if write_stats: 
6804                      for i, corr_data_i in enumerate(corr_data): 
6805                          data, methods, glob_inis = corr_data[i] 
6806                          data_x, data_y = data 
6807                          method_x, method_y = methods 
6808                          glob_ini_x, glob_ini_y = glob_inis 
6809   
6810                          file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6811   
6812                          if selection == None: 
6813                              file_name = file_name_ini + '_all.txt' 
6814                          else: 
6815                              file_name = file_name_ini + '_sel.txt' 
6816                          path = RDR.results_dir 
6817                          data = extract_data(file=file_name, dir=path) 
6818   
6819                          # Loop over the lines. 
6820                          for i, data_i in enumerate(data): 
6821                              print(i, data_i) 
6822   
6823          # Try plot some minimisation statistics. 
6824          if True: 
6825              # Collect param values. 
6826              #selections = [None, ':2,3'] 
6827              selections = [None, ':2,3'] 
6828              for selection in selections: 
6829                  analysis = 'min_ind' 
6830                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6831                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6832   
6833                  # Get param stats. 
6834                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6835   
6836                  ## Plot R2eff stats 
6837                  write_stats = True 
6838                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6839   
6840                  # Open stat file. 
6841                  if write_stats: 
6842                      if selection == None: 
6843                          file_name = '%s_stat_all.txt' % (analysis) 
6844                      else: 
6845                          file_name = '%s_stat_sel.txt' % (analysis) 
6846                      path = RDR.results_dir 
6847                      data = extract_data(file=file_name, dir=path) 
6848   
6849                      # Loop over the lines. 
6850                      for i, data_i in enumerate(data): 
6851                          print(i, data_i) 
6852   
6853   
6854          # Do minimisation clustered. 
6855          if True: 
6856              methods = ['FT', 'MDD'] 
6857              # Now calculate R2eff. 
6858              RDR.calc_r2eff(methods=methods, list_glob_ini=[128, 126]) 
6859   
6860              min_methods = [['FT'], ['MDD']] 
6861              min_list_glob_ini = [[128], list(range(126, 130, 2))[::-1]] 
6862   
6863              #min_methods = [['FT']] 
6864              #min_list_glob_ini = [[128]] 
6865              selection = ':2,3' 
6866   
6867              for i, methods in enumerate(min_methods): 
6868                  list_glob_ini = min_list_glob_ini[i] 
6869   
6870                  if True: 
6871                      # First get data. 
6872                      if True: 
6873                          # First load all data. 
6874                          RDR.calc_r2eff(methods=methods, list_glob_ini=list_glob_ini) 
6875   
6876                      # Then select spins. 
6877                      if True: 
6878                          # Deselect all spins. 
6879                          RDR.deselect_all(methods=methods, model='setup', model_from=MODEL_R2EFF, analysis='grid_setup', analysis_from='int', list_glob_ini=list_glob_ini, force=True) 
6880   
6881                          RDR.select_spin(spin_id=selection, methods=methods, model='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6882   
6883                      # Then preset values. 
6884                      if True: 
6885                          # Set k_AB for Grid search. 
6886                          RDR.value_set(methods=methods, val=1000., param='kex', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6887                          RDR.value_set(methods=methods, val=0.95, param='pA', model=MODEL_CR72, model_from='setup', analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6888   
6889                      # Then set R20 
6890                      if True: 
6891                          # Set R20 from min R2eff in preparation for Grid search. 
6892                          RDR.r20_from_min_r2eff(methods=methods, model=MODEL_CR72, analysis='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6893   
6894                      # Check and print parameters. 
6895                      if True: 
6896                          # Print for pipe name 
6897                          method = methods[0] 
6898                          glob_ini = list_glob_ini[0] 
6899   
6900                          test_pipe_name = RDR.name_pipe(method=method, model=MODEL_CR72, analysis='grid_setup', glob_ini=glob_ini) 
6901                          RDR.spin_display_params(pipe_name=test_pipe_name) 
6902   
6903                      # Then Grid search. 
6904                      if True: 
6905                          # Do Grid search. 
6906                          RDR.minimise_grid_search(inc=200, verbosity=1, methods=methods, model=MODEL_CR72, analysis='grid', analysis_from='grid_setup', list_glob_ini=list_glob_ini, force=True) 
6907   
6908                      # Then cluster spins. 
6909                      if True: 
6910                          RDR.cluster_spins(spin_id=selection, methods=methods, model=MODEL_CR72, analysis='grid', list_glob_ini=list_glob_ini, force=True) 
6911   
6912                  # Then Minimise. 
6913                  if True: 
6914                      # Minimise 
6915                      RDR.opt_max_iterations = int(1e2) 
6916                      RDR.minimise_execute(methods=methods, model=MODEL_CR72, analysis='min', analysis_from='grid', list_glob_ini=list_glob_ini, force=False) 
6917   
6918          # Plot statistics. 
6919          # Try plot some minimisation correlations. 
6920          if True: 
6921              selection = ':2,3' 
6922              # Collect param values. 
6923              analysis = 'min' 
6924              min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6925              min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6926   
6927              fig1 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 128]] 
6928              fig2 = [[min_ft_sel, min_mdd_sel], ['FT', 'MDD'], [128, 126]] 
6929              corr_data = [fig1, fig2] 
6930   
6931              write_stats = True 
6932              RDR.plot_min_corr(corr_data=corr_data, show=False, write_stats=write_stats) 
6933   
6934              # Open stat file. 
6935              if write_stats: 
6936                  for i, corr_data_i in enumerate(corr_data): 
6937                      data, methods, glob_inis = corr_data[i] 
6938                      data_x, data_y = data 
6939                      method_x, method_y = methods 
6940                      glob_ini_x, glob_ini_y = glob_inis 
6941   
6942                      file_name_ini = '%s_%s_%s_%s_%s' % (analysis, method_x, glob_ini_x, method_y, glob_ini_y) 
6943   
6944                      if selection == None: 
6945                          file_name = file_name_ini + '_all.txt' 
6946                      else: 
6947                          file_name = file_name_ini + '_sel.txt' 
6948                      path = RDR.results_dir 
6949                      data = extract_data(file=file_name, dir=path) 
6950   
6951                      # Loop over the lines. 
6952                      for i, data_i in enumerate(data): 
6953                          print(i, data_i) 
6954   
6955          # Try plot some minimisation statistics. 
6956          if True: 
6957              # Collect param values. 
6958              selections = [':2,3'] 
6959              for selection in selections: 
6960                  analysis = 'min' 
6961                  min_ft_sel = RDR.col_min(method='FT', model=MODEL_CR72, analysis=analysis, list_glob_ini=[128], selection=selection) 
6962                  min_mdd_sel = RDR.col_min(method='MDD', model=MODEL_CR72, analysis=analysis, list_glob_ini=list(range(126, 130, 2))[::-1], selection=selection) 
6963   
6964                  # Get param stats. 
6965                  min_stat_dic = RDR.get_min_stat_dic(list_r2eff_dics=[min_ft_sel, min_mdd_sel], list_glob_ini=[128, 126]) 
6966   
6967                  ## Plot R2eff stats 
6968                  write_stats = True 
6969                  RDR.plot_min_stat(min_stat_dic=min_stat_dic, methods=['FT', 'MDD'], list_glob_ini=[128, 126, 6], show=False, write_stats=write_stats) 
6970   
6971                  # Open stat file. 
6972                  if write_stats: 
6973                      if selection == None: 
6974                          file_name = '%s_stat_all.txt' % (analysis) 
6975                      else: 
6976                          file_name = '%s_stat_sel.txt' % (analysis) 
6977                      path = RDR.results_dir 
6978                      data = extract_data(file=file_name, dir=path) 
6979   
6980                      # Loop over the lines. 
6981                      for i, data_i in enumerate(data): 
6982                          print(i, data_i) 
6983   
6984   
6985 -    def test_r1rho_kjaergaard_auto(self): 
6986          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
6987   
6988          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
6989   
6990          This uses the automatic analysis. 
6991   
6992          """ 
6993   
6994          # Cluster residues 
6995          cluster_ids = [ 
6996          ":13@N", 
6997          ":15@N", 
6998          ":16@N", 
6999          ":25@N", 
7000          ":26@N", 
7001          ":28@N", 
7002          ":39@N", 
7003          ":40@N", 
7004          ":41@N", 
7005          ":43@N", 
7006          ":44@N", 
7007          ":45@N", 
7008          ":49@N", 
7009          ":52@N", 
7010          ":53@N"] 
7011   
7012          # Load the data. 
7013          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
7014   
7015          # Test some of the sequence. 
7016          self.assertEqual(len(cdp.mol), 1) 
7017          self.assertEqual(cdp.mol[0].name, None) 
7018          self.assertEqual(len(cdp.mol[0].res), 48) 
7019   
7020          # Test the chemical shift data. 
7021          cs = [122.223, 122.162, 114.250, 125.852, 118.626, 117.449, 119.999, 122.610, 118.602, 118.291, 115.393, 
7022          121.288, 117.448, 116.378, 116.316, 117.263, 122.211, 118.748, 118.103, 119.421, 119.317, 119.386, 117.279, 
7023          122.103, 120.038, 116.698, 111.811, 118.639, 118.285, 121.318, 117.770, 119.948, 119.759, 118.314, 118.160, 
7024          121.442, 118.714, 113.080, 125.706, 119.183, 120.966, 122.361, 126.675, 117.069, 120.875, 109.372, 119.811, 126.048] 
7025   
7026          i = 0 
7027          for spin, spin_id in spin_loop(return_id=True): 
7028              # Check the chemical shift. 
7029              self.assertEqual(spin.chemical_shift, cs[i]) 
7030   
7031              # Increment the index. 
7032              i += 1 
7033   
7034          # Initialize counter 
7035          i = 0 
7036          j = 0 
7037          # Count instances of select/deselect 
7038          for curspin, mol_name, res_num, res_name, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=False): 
7039              if curspin.select == True: 
7040                  i += 1 
7041              if curspin.select == False: 
7042                  j += 1 
7043   
7044          # Test number of selected/deselected spins. 
7045          self.assertEqual(i, len(cluster_ids)) 
7046          self.assertEqual(j, 48-len(cluster_ids)) 
7047   
7048          # Check the initial setup. 
7049          self.assertEqual(cdp.mol[0].res[7].num, 13) 
7050          self.assertEqual(cdp.mol[0].res[7].spin[0].kex, ds.guess[':13@N'][6]) 
7051          self.assertEqual(cdp.mol[0].res[7].spin[0].ri_data['R1'], ds.ref[':13@N'][2]) 
7052   
7053          self.assertEqual(cdp.mol[0].res[9].num, 15) 
7054          self.assertEqual(cdp.mol[0].res[9].spin[0].kex, ds.guess[':15@N'][6]) 
7055          self.assertEqual(cdp.mol[0].res[9].spin[0].ri_data['R1'], ds.ref[':15@N'][2]) 
7056   
7057          self.assertEqual(cdp.mol[0].res[10].num, 16) 
7058          self.assertEqual(cdp.mol[0].res[10].spin[0].kex, ds.guess[':16@N'][6]) 
7059          self.assert_(hasattr(cdp.mol[0].res[10].spin[0], 'ri_data')) 
7060   
7061          self.assertEqual(cdp.mol[0].res[16].num, 25) 
7062          self.assertEqual(cdp.mol[0].res[16].spin[0].kex, ds.guess[':25@N'][6]) 
7063          self.assert_(hasattr(cdp.mol[0].res[16].spin[0], 'ri_data')) 
7064   
7065          self.assertEqual(cdp.mol[0].res[17].num, 26) 
7066          self.assertEqual(cdp.mol[0].res[17].spin[0].kex, ds.guess[':26@N'][6]) 
7067          self.assert_(hasattr(cdp.mol[0].res[17].spin[0], 'ri_data')) 
7068   
7069          self.assertEqual(cdp.mol[0].res[19].num, 28) 
7070          self.assertEqual(cdp.mol[0].res[19].spin[0].kex, ds.guess[':28@N'][6]) 
7071          self.assert_(hasattr(cdp.mol[0].res[19].spin[0], 'ri_data')) 
7072   
7073          self.assertEqual(cdp.mol[0].res[29].num, 39) 
7074          self.assertEqual(cdp.mol[0].res[29].spin[0].kex, ds.guess[':39@N'][6]) 
7075          self.assert_(hasattr(cdp.mol[0].res[29].spin[0], 'ri_data')) 
7076   
7077          self.assertEqual(cdp.mol[0].res[30].num, 40) 
7078          self.assertEqual(cdp.mol[0].res[30].spin[0].kex, ds.guess[':40@N'][6]) 
7079          self.assert_(hasattr(cdp.mol[0].res[30].spin[0], 'ri_data')) 
7080   
7081          self.assertEqual(cdp.mol[0].res[31].num, 41) 
7082          self.assertEqual(cdp.mol[0].res[31].spin[0].kex, ds.guess[':41@N'][6]) 
7083          self.assert_(hasattr(cdp.mol[0].res[31].spin[0], 'ri_data')) 
7084   
7085          self.assertEqual(cdp.mol[0].res[33].num, 43) 
7086          self.assertEqual(cdp.mol[0].res[33].spin[0].kex, ds.guess[':43@N'][6]) 
7087          self.assert_(hasattr(cdp.mol[0].res[33].spin[0], 'ri_data')) 
7088   
7089          self.assertEqual(cdp.mol[0].res[34].num, 44) 
7090          self.assertEqual(cdp.mol[0].res[34].spin[0].kex, ds.guess[':44@N'][6]) 
7091          self.assert_(hasattr(cdp.mol[0].res[34].spin[0], 'ri_data')) 
7092   
7093          self.assertEqual(cdp.mol[0].res[35].num, 45) 
7094          self.assertEqual(cdp.mol[0].res[35].spin[0].kex, ds.guess[':45@N'][6]) 
7095          self.assert_(hasattr(cdp.mol[0].res[35].spin[0], 'ri_data')) 
7096   
7097          self.assertEqual(cdp.mol[0].res[38].num, 49) 
7098          self.assertEqual(cdp.mol[0].res[38].spin[0].kex, ds.guess[':49@N'][6]) 
7099          self.assert_(hasattr(cdp.mol[0].res[38].spin[0], 'ri_data')) 
7100   
7101          self.assertEqual(cdp.mol[0].res[41].num, 52) 
7102          self.assertEqual(cdp.mol[0].res[41].spin[0].kex, ds.guess[':52@N'][6]) 
7103          self.assert_(hasattr(cdp.mol[0].res[41].spin[0], 'ri_data')) 
7104   
7105          self.assertEqual(cdp.mol[0].res[42].num, 53) 
7106          self.assertEqual(cdp.mol[0].res[42].spin[0].kex, ds.guess[':53@N'][6]) 
7107          self.assert_(hasattr(cdp.mol[0].res[42].spin[0], 'ri_data')) 
7108   
7109          # The dispersion models. 
7110          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
7111   
7112          # The grid search size (the number of increments per dimension). 
7113          GRID_INC = 4 
7114   
7115          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7116          MC_NUM = 3 
7117   
7118          # Model selection technique. 
7119          MODSEL = 'AIC' 
7120   
7121          # Execute the auto-analysis (fast). 
7122          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7123          OPT_FUNC_TOL = 1e-1 
7124          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7125          OPT_MAX_ITERATIONS = 1000 
7126          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7127   
7128          result_dir_name = ds.tmpdir 
7129   
7130          # Make all spins free 
7131          for curspin in cluster_ids: 
7132              self.interpreter.relax_disp.cluster('free spins', curspin) 
7133              # Shut them down 
7134              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7135   
7136          # Select only a subset of spins for global fitting 
7137          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
7138          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
7139   
7140          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
7141          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
7142   
7143          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7144          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
7145   
7146          # Run the analysis. 
7147          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
7148   
7149          # Check the kex value of residue 52 
7150          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
7151   
7152          # Print results for each model. 
7153          print("\n\n################") 
7154          print("Printing results") 
7155          print("################\n") 
7156          for model in MODELS: 
7157              # Skip R2eff model. 
7158              if model == MODEL_R2EFF: 
7159                  continue 
7160   
7161              # Switch to pipe. 
7162              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
7163              print("\nModel: %s" % (model)) 
7164   
7165              # Loop over the spins. 
7166              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7167                  # Generate spin string. 
7168                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
7169   
7170                  # Loop over the parameters. 
7171                  print("Optimised parameters for spin: %s" % (spin_string)) 
7172                  for param in cur_spin.params + ['chi2']: 
7173                      # Get the value. 
7174                      if param in ['r1', 'r2']: 
7175                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
7176                              # Generate the R20 key. 
7177                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
7178   
7179                              # Get the value. 
7180                              value = getattr(cur_spin, param)[r20_key] 
7181   
7182                              # Print value. 
7183                              print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
7184   
7185                      # For all other parameters. 
7186                      else: 
7187                          # Get the value. 
7188                          value = getattr(cur_spin, param) 
7189   
7190                          # Print value. 
7191                          print("%-10s %-6s %-6s %3.3f" % ("Parameter:", param, "Value:", value)) 
7192   
7193          # Print the final pipe. 
7194          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % ('final')) 
7195          print("\nFinal pipe") 
7196   
7197   
7198 -    def test_r1rho_kjaergaard_auto_check_graphs(self): 
7199          """Check of plot_disp_curves() function, after optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'R2eff' model. 
7200   
7201          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7202   
7203          This uses the automatic analysis. 
7204   
7205          """ 
7206   
7207          # Cluster residues 
7208          cluster_ids = [ 
7209          ":52@N"] 
7210   
7211          # Load the data. 
7212          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids) 
7213   
7214          # The dispersion models. 
7215          MODELS = [MODEL_R2EFF] 
7216   
7217          # The grid search size (the number of increments per dimension). 
7218          GRID_INC = 4 
7219   
7220          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7221          MC_NUM = 3 
7222   
7223          # Model selection technique. 
7224          MODSEL = 'AIC' 
7225   
7226          # Execute the auto-analysis (fast). 
7227          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7228          OPT_FUNC_TOL = 1e-1 
7229          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7230          OPT_MAX_ITERATIONS = 1000 
7231          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7232   
7233          result_dir_name = ds.tmpdir 
7234   
7235          # Make all spins free 
7236          for curspin in cluster_ids: 
7237              self.interpreter.relax_disp.cluster('free spins', curspin) 
7238              # Shut them down 
7239              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7240   
7241          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7242   
7243          # Run the analysis. 
7244          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
7245   
7246          # Check the graphs produced. 
7247          graph_comb = [ 
7248          [Y_AXIS_R2_EFF, X_AXIS_DISP, INTERPOLATE_DISP], 
7249          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_DISP], 
7250          [Y_AXIS_R2_R1RHO, X_AXIS_W_EFF, INTERPOLATE_DISP], 
7251          [Y_AXIS_R2_EFF, X_AXIS_THETA, INTERPOLATE_OFFSET] 
7252          ] 
7253   
7254          # Define expected folder names. 
7255          result_folders = MODELS 
7256   
7257          # Assign spin_id. 
7258          spin_id = ':52@N' 
7259   
7260          # Loop over result folders. 
7261          for result_folder in result_folders: 
7262              # Skip the model R2eff, which does not produce graphs. 
7263              if result_folder == MODEL_R2EFF: 
7264                  continue 
7265   
7266              # Loop over graphs. 
7267              for y_axis, x_axis, interpolate in graph_comb: 
7268                  # Determine file name: 
7269                  file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7270   
7271                  # Make the file name. 
7272                  file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7273   
7274                  # Get the file path. 
7275                  file_path = get_file_path(file_name, result_dir_name+sep+result_folder) 
7276   
7277                  print("Testing file access to graph: %s"%file_path) 
7278                  self.assert_(access(file_path, F_OK)) 
7279   
7280          # Start testing all possible combinations of graphs. 
7281          y_axis_types = [Y_AXIS_R2_EFF, Y_AXIS_R2_R1RHO] 
7282          x_axis_types = [X_AXIS_DISP, X_AXIS_THETA, X_AXIS_W_EFF] 
7283          interpolate_types = [INTERPOLATE_DISP, INTERPOLATE_OFFSET] 
7284   
7285          result_dir_name = ds.tmpdir 
7286   
7287          # Loop through all possible combinations of y_axis, x_axis and interpolation. 
7288          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep+'check_graphs' 
7289   
7290          for result_folder in result_folders: 
7291              # Skip the model R2eff, which does not produce graphs. 
7292              if result_folder == MODEL_R2EFF: 
7293                  continue 
7294   
7295              for y_axis in y_axis_types: 
7296                  for x_axis in x_axis_types: 
7297                      for interpolate in interpolate_types: 
7298                          # Determine file name: 
7299                          file_name_ini = return_grace_file_name_ini(y_axis=y_axis, x_axis=x_axis, interpolate=interpolate) 
7300   
7301                          # Make the file name. 
7302                          file_name = "%s%s.agr" % (file_name_ini, spin_id.replace('#', '_').replace(':', '_').replace('@', '_')) 
7303   
7304                          # Write the curves. 
7305                          dir = result_dir_name+sep+result_folder 
7306                          print("Plotting combination of %s, %s, %s"%(y_axis, x_axis, interpolate)) 
7307                          self.interpreter.relax_disp.plot_disp_curves(dir=dir, y_axis=y_axis, x_axis=x_axis, interpolate=interpolate, force=True) 
7308   
7309                          # Get the file path. 
7310                          file_path = get_file_path(file_name, dir) 
7311   
7312                          # Test the plot file exists. 
7313                          print("Testing file access to graph: %s"%file_path) 
7314                          self.assert_(access(file_path, F_OK)) 
7315   
7316                          # Now open, and compare content, line by line. 
7317                          file_prod = open(file_path) 
7318                          lines_prod = file_prod.readlines() 
7319                          file_prod.close() 
7320   
7321                          # Define file to compare against. 
7322                          dir_comp = data_path+sep+result_folder 
7323                          file_path_comp = get_file_path(file_name, dir_comp) 
7324                          file_comp = open(file_path_comp) 
7325                          lines_comp = file_comp.readlines() 
7326                          file_comp.close() 
7327   
7328                          # Assert number of lines is equal. 
7329                          self.assertEqual(len(lines_prod), len(lines_comp)) 
7330                          for j in range(len(lines_prod)): 
7331                              # Make the string test 
7332                              first_char = lines_prod[j][0] 
7333                              if first_char in ["@", "&"]: 
7334                                  self.assertEqual(lines_prod[j], lines_comp[j]) 
7335                              else: 
7336                                  # Split string in x, y, error. 
7337                                  # The error would change per run. 
7338                                  x_prod, y_prod, y_prod_err = lines_prod[j].split() 
7339                                  x_comp, y_comp, y_comp_err = lines_comp[j].split() 
7340                                  self.assertAlmostEqual(float(x_prod), float(x_comp)) 
7341                                  self.assertAlmostEqual(float(y_prod), float(y_comp)) 
7342   
7343   
7344 -    def test_r1rho_kjaergaard_missing_r1(self): 
7345          """Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
7346   
7347          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
7348   
7349          This uses the automatic analysis, with missing loading R1. 
7350   
7351          """ 
7352   
7353          # Cluster residues 
7354          cluster_ids = [ 
7355          ":13@N", 
7356          ":15@N", 
7357          ":16@N", 
7358          ":25@N", 
7359          ":26@N", 
7360          ":28@N", 
7361          ":39@N", 
7362          ":40@N", 
7363          ":41@N", 
7364          ":43@N", 
7365          ":44@N", 
7366          ":45@N", 
7367          ":49@N", 
7368          ":52@N", 
7369          ":53@N"] 
7370   
7371          # Load the data. 
7372          self.setup_r1rho_kjaergaard(cluster_ids=cluster_ids, read_R1=False) 
7373   
7374          # The dispersion models. 
7375          MODELS = [MODEL_R2EFF, MODEL_NOREX, MODEL_DPL94, MODEL_TP02, MODEL_TAP03, MODEL_MP05, MODEL_NS_R1RHO_2SITE] 
7376   
7377          # The grid search size (the number of increments per dimension). 
7378          GRID_INC = None 
7379   
7380          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7381          MC_NUM = 3 
7382   
7383          # Model selection technique. 
7384          MODSEL = 'AIC' 
7385   
7386          # Execute the auto-analysis (fast). 
7387          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7388          OPT_FUNC_TOL = 1e-25 
7389          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7390          OPT_MAX_ITERATIONS = 10000000 
7391          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7392   
7393          result_dir_name = ds.tmpdir 
7394   
7395          # Make all spins free 
7396          for curspin in cluster_ids: 
7397              self.interpreter.relax_disp.cluster('free spins', curspin) 
7398              # Shut them down 
7399              self.interpreter.deselect.spin(spin_id=curspin, change_all=False) 
7400   
7401          # Select only a subset of spins for global fitting 
7402          #self.interpreter.select.spin(spin_id=':41@N', change_all=False) 
7403          #self.interpreter.relax_disp.cluster('model_cluster', ':41@N') 
7404   
7405          #self.interpreter.select.spin(spin_id=':40@N', change_all=False) 
7406          #self.interpreter.relax_disp.cluster('model_cluster', ':40@N') 
7407   
7408          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
7409          #self.interpreter.relax_disp.cluster('model_cluster', ':52@N') 
7410   
7411          # Point to directory with R2eff values, with 2000 MC simulations. 
7412          prev_data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' +sep+ "check_graphs" +sep+ "mc_2000" 
7413   
7414          r1_fit = True 
7415   
7416          # Run the analysis. 
7417          relax_disp.Relax_disp(pipe_name=ds.pipe_name, pipe_bundle=ds.pipe_bundle, results_dir=result_dir_name, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, pre_run_dir=prev_data_path, r1_fit=r1_fit) 
7418   
7419          # Verify the data. 
7420          self.verify_r1rho_kjaergaard_missing_r1(models=MODELS, result_dir_name=result_dir_name, r2eff_estimate='MC2000') 
7421   
7422   
7423 -    def test_r2eff_read(self): 
7424          """Test the operation of the relax_disp.r2eff_read user function.""" 
7425   
7426          # The path to the data files. 
7427          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Hansen'+sep+'800_MHz' 
7428   
7429          # Read the sequence data. 
7430          self.interpreter.sequence.read(file='66.667.in', dir=data_path, res_num_col=1) 
7431   
7432          # The ID. 
7433          id = 'test' 
7434   
7435          # Set up the metadata. 
7436          self.interpreter.spectrometer.frequency(id=id, frq=800e6) 
7437          self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7438   
7439          # Try reading the file. 
7440          self.interpreter.relax_disp.r2eff_read(id=id, file='66.667.in', dir=data_path, disp_frq=66.667, res_num_col=1, data_col=2, error_col=3) 
7441   
7442          # Check the global data. 
7443          data = [ 
7444              ['cpmg_frqs', {'test': 66.667}], 
7445              ['cpmg_frqs_list', [66.667]], 
7446              ['dispersion_points', 1], 
7447              ['exp_type', {'test': 'SQ CPMG'}], 
7448              ['exp_type_list', ['SQ CPMG']], 
7449              ['spectrometer_frq', {'test': 800000000.0}], 
7450              ['spectrometer_frq_count', 1], 
7451              ['spectrometer_frq_list', [800000000.0]], 
7452              ['spectrum_ids', ['test']] 
7453          ] 
7454          for name, value in data: 
7455              # Does it exist? 
7456              self.assert_(hasattr(cdp, name)) 
7457   
7458              # Check the object. 
7459              obj = getattr(cdp, name) 
7460              self.assertEqual(obj, value) 
7461   
7462          # Check the spin data. 
7463          data = [ 
7464              [1,       2.3035747e+04, 8.5467725e+01], 
7465              [2,       9.9629762e+04, 2.8322033e+02], 
7466              [3,       9.5663137e+04, 2.8632929e+02], 
7467              [4,       1.7089893e+05, 3.1089428e+02], 
7468              [5,       4.7323876e+04, 1.0084269e+02], 
7469              [6,       2.0199122e+04, 1.0135220e+02], 
7470              [7,       1.6655488e+05, 3.1609061e+02], 
7471              [8,       9.0061074e+04, 1.9176585e+02], 
7472              [10,      8.4726204e+04, 2.8898155e+02], 
7473              [11,      1.5050233e+05, 4.3138029e+02], 
7474              [12,      9.2998531e+04, 3.0440191e+02], 
7475              [13,      1.6343507e+05, 3.3144097e+02], 
7476              [14,      1.0137301e+05, 3.7314642e+02], 
7477              [15,      8.3407837e+04, 1.6546473e+02], 
7478              [16,      1.3819126e+05, 3.3388517e+02], 
7479              [17,      1.1010490e+05, 3.5639222e+02], 
7480              [18,      9.4324035e+04, 3.2343585e+02], 
7481              [19,      1.1135179e+05, 3.0706671e+02], 
7482              [20,      7.6339410e+04, 1.7377460e+02], 
7483              [21,      6.2008453e+04, 1.7327150e+02], 
7484              [22,      1.0590404e+05, 2.4814635e+02], 
7485              [23,      1.0630198e+05, 2.3601100e+02], 
7486              [24,      7.2996320e+04, 1.4952465e+02], 
7487              [25,      9.5486742e+04, 2.7080766e+02], 
7488              [26,      5.8067989e+04, 1.6820462e+02], 
7489              [27,     -1.7168510e+04, 2.2519560e+02], 
7490              [28,      1.6891473e+05, 2.3497525e+02], 
7491              [29,      9.4038555e+04, 2.0357593e+02], 
7492              [30,      2.1386951e+04, 2.2153532e+02], 
7493              [31,      9.3982899e+04, 2.0937056e+02], 
7494              [32,      8.6097484e+04, 2.3868467e+02], 
7495              [33,      1.0194337e+05, 2.7370704e+02], 
7496              [34,      8.5683111e+04, 2.0838076e+02], 
7497              [35,      8.6985768e+04, 2.0889310e+02], 
7498              [36,      8.6011237e+04, 1.7498390e+02], 
7499              [37,      1.0984097e+05, 2.7622998e+02], 
7500              [38,      8.7017879e+04, 2.6547994e+02], 
7501              [39,      9.1682649e+04, 5.2777676e+02], 
7502              [40,      7.6370440e+04, 1.9873214e+02], 
7503              [41,      9.1393531e+04, 2.4483824e+02], 
7504              [42,      1.1017111e+05, 2.8020699e+02], 
7505              [43,      9.4552366e+04, 3.4394150e+02], 
7506              [44,      1.2858281e+05, 6.8449252e+02], 
7507              [45,      7.4583525e+04, 1.9544210e+02], 
7508              [46,      9.2087490e+04, 2.0491066e+02], 
7509              [47,      9.7507255e+04, 2.5162839e+02], 
7510              [48,      1.0033842e+05, 2.7566430e+02], 
7511              [49,      1.3048305e+05, 2.6797466e+02], 
7512              [50,      1.0546796e+05, 1.9304384e+02], 
7513              [51,      9.3099697e+04, 2.0773311e+02], 
7514              [52,      4.6863758e+04, 1.3169068e+02], 
7515              [53,      6.1055806e+04, 1.5448477e+02], 
7516              [55,      6.8629994e+04, 1.6868673e+02], 
7517              [56,      1.1005552e+05, 2.1940465e+02], 
7518              [57,      1.0572760e+05, 1.9768486e+02], 
7519              [58,      1.1176950e+05, 3.0009610e+02], 
7520              [59,      9.8758603e+04, 3.3803895e+02], 
7521              [60,      9.9517201e+04, 3.5137994e+02], 
7522              [61,      5.4357946e+04, 2.5896579e+02], 
7523              [62,      1.0899978e+05, 2.8720371e+02], 
7524              [63,      8.4549759e+04, 4.1401837e+02], 
7525              [64,      5.5014550e+04, 2.1135781e+02], 
7526              [65,      8.0569666e+04, 2.3249709e+02], 
7527              [66,      1.2936610e+05, 3.5218725e+02], 
7528              [67,      3.6438010e+04, 8.7924003e+01], 
7529              [70,      3.8763157e+04, 1.3325040e+02], 
7530              [71,      8.5711411e+04, 2.9316183e+02], 
7531              [72,      3.3211541e+04, 1.2182123e+02], 
7532              [73,      3.2070576e+04, 1.2305430e+02] 
7533          ] 
7534          for res_num, value, error in data: 
7535              # Get the spin. 
7536              spin = return_spin(spin_id=":%s"%res_num) 
7537   
7538              # Check the values. 
7539              self.assertEqual(spin.r2eff['sq_cpmg_800.00000000_0.000_66.667'], value) 
7540              self.assertEqual(spin.r2eff_err['sq_cpmg_800.00000000_0.000_66.667'], error) 
7541   
7542   
7543 -    def test_r2eff_read_spin(self): 
7544          """Test the operation of the relax_disp.r2eff_read_spin user function.""" 
7545   
7546          # The path to the data files. 
7547          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Korzhnev_et_al_2005' 
7548   
7549          # Generate the sequence. 
7550          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='H') 
7551          self.interpreter.spin.create(res_name='Asp', res_num=9, spin_name='N') 
7552          self.interpreter.spin.isotope('1H', spin_id='@H') 
7553          self.interpreter.spin.isotope('15N', spin_id='@N') 
7554   
7555          # Build the experiment IDs. 
7556          H_disp_points = [67.0, 133.0, 267.0, 400.0, 533.0, 667.0, 800.0, 933.0, 1067.0, 1600.0, 2133.0, 2667.0] 
7557          N_disp_points = [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0] 
7558          ids = [] 
7559          for value in H_disp_points: 
7560              ids.append('1H_CPMG_%s' % value) 
7561          for value in N_disp_points: 
7562              ids.append('15N_CPMG_%s' % value) 
7563          print("\n\nThe experiment IDs are %s." % ids) 
7564   
7565          # Set up the metadata for the experiments. 
7566          for id in ids: 
7567              self.interpreter.spectrometer.frequency(id=id, frq=500e6) 
7568              self.interpreter.relax_disp.exp_type(spectrum_id=id, exp_type='SQ CPMG') 
7569          for value in H_disp_points: 
7570              self.interpreter.relax_disp.cpmg_setup(spectrum_id='1H_CPMG_%s' % value, cpmg_frq=value) 
7571          for value in N_disp_points: 
7572              self.interpreter.relax_disp.cpmg_setup(spectrum_id='15N_CPMG_%s' % value, cpmg_frq=value) 
7573   
7574          # Loop over the experiments. 
7575          for id, file, spin_id in [['1H_CPMG', 'hs_500.res', ':9@H'], ['15N_CPMG', 'ns_500.res', ':9@N']]: 
7576              # Try reading the file. 
7577              self.interpreter.relax_disp.r2eff_read_spin(id=id, file=file, dir=data_path, spin_id=spin_id, disp_point_col=1, data_col=2, error_col=3) 
7578   
7579          # Check the global data. 
7580          data = [ 
7581              ['cpmg_frqs', {'1H_CPMG_667.0': 667.0, '1H_CPMG_1067.0': 1067.0, '15N_CPMG_350.0': 350.0, '1H_CPMG_933.0': 933.0, '15N_CPMG_50.0': 50.0, '15N_CPMG_100.0': 100.0, '1H_CPMG_400.0': 400.0, '1H_CPMG_533.0': 533.0, '1H_CPMG_800.0': 800.0, '15N_CPMG_900.0': 900.0, '15N_CPMG_150.0': 150.0, '15N_CPMG_800.0': 800.0, '1H_CPMG_267.0': 267.0, '1H_CPMG_2667.0': 2667.0, '15N_CPMG_300.0': 300.0, '1H_CPMG_133.0': 133.0, '15N_CPMG_700.0': 700.0, '1H_CPMG_67.0': 67.0, '15N_CPMG_400.0': 400.0, '15N_CPMG_250.0': 250.0, '1H_CPMG_2133.0': 2133.0, '1H_CPMG_1600.0': 1600.0, '15N_CPMG_200.0': 200.0, '15N_CPMG_1000.0': 1000.0, '15N_CPMG_500.0': 500.0, '15N_CPMG_600.0': 600.0}], 
7582              ['cpmg_frqs_list', [50.0, 67.0, 100.0, 133.0, 150.0, 200.0, 250.0, 267.0, 300.0, 350.0, 400.0, 500.0, 533.0, 600.0, 667.0, 700.0, 800.0, 900.0, 933.0, 1000.0, 1067.0, 1600.0, 2133.0, 2667.0]], 
7583              ['dispersion_points', 24], 
7584              ['exp_type', {'1H_CPMG_667.0': 'SQ CPMG', '1H_CPMG_1067.0': 'SQ CPMG', '15N_CPMG_350.0': 'SQ CPMG', '1H_CPMG_933.0': 'SQ CPMG', '15N_CPMG_50.0': 'SQ CPMG', '15N_CPMG_100.0': 'SQ CPMG', '1H_CPMG_400.0': 'SQ CPMG', '1H_CPMG_533.0': 'SQ CPMG', '1H_CPMG_800.0': 'SQ CPMG', '15N_CPMG_900.0': 'SQ CPMG', '15N_CPMG_150.0': 'SQ CPMG', '15N_CPMG_800.0': 'SQ CPMG', '1H_CPMG_267.0': 'SQ CPMG', '1H_CPMG_2667.0': 'SQ CPMG', '15N_CPMG_300.0': 'SQ CPMG', '1H_CPMG_133.0': 'SQ CPMG', '15N_CPMG_700.0': 'SQ CPMG', '1H_CPMG_67.0': 'SQ CPMG', '15N_CPMG_400.0': 'SQ CPMG', '15N_CPMG_250.0': 'SQ CPMG', '1H_CPMG_2133.0': 'SQ CPMG', '1H_CPMG_1600.0': 'SQ CPMG', '15N_CPMG_200.0': 'SQ CPMG', '15N_CPMG_1000.0': 'SQ CPMG', '15N_CPMG_500.0': 'SQ CPMG', '15N_CPMG_600.0': 'SQ CPMG'}], 
7585              ['exp_type_list', ['SQ CPMG']], 
7586              ['spectrometer_frq', {'1H_CPMG_667.0': 500000000.0, '1H_CPMG_1067.0': 500000000.0, '15N_CPMG_350.0': 500000000.0, '1H_CPMG_933.0': 500000000.0, '15N_CPMG_50.0': 500000000.0, '15N_CPMG_100.0': 500000000.0, '1H_CPMG_400.0': 500000000.0, '1H_CPMG_533.0': 500000000.0, '1H_CPMG_800.0': 500000000.0, '15N_CPMG_900.0': 500000000.0, '15N_CPMG_150.0': 500000000.0, '15N_CPMG_800.0': 500000000.0, '1H_CPMG_267.0': 500000000.0, '1H_CPMG_2667.0': 500000000.0, '15N_CPMG_300.0': 500000000.0, '1H_CPMG_133.0': 500000000.0, '15N_CPMG_700.0': 500000000.0, '1H_CPMG_67.0': 500000000.0, '15N_CPMG_400.0': 500000000.0, '15N_CPMG_250.0': 500000000.0, '1H_CPMG_2133.0': 500000000.0, '1H_CPMG_1600.0': 500000000.0, '15N_CPMG_200.0': 500000000.0, '15N_CPMG_1000.0': 500000000.0, '15N_CPMG_500.0': 500000000.0, '15N_CPMG_600.0': 500000000.0}], 
7587              ['spectrometer_frq_count', 1], 
7588              ['spectrometer_frq_list', [500000000.0]], 
7589              ['spectrum_ids', ['1H_CPMG_67.0', '1H_CPMG_133.0', '1H_CPMG_267.0', '1H_CPMG_400.0', '1H_CPMG_533.0', '1H_CPMG_667.0', '1H_CPMG_800.0', '1H_CPMG_933.0', '1H_CPMG_1067.0', '1H_CPMG_1600.0', '1H_CPMG_2133.0', '1H_CPMG_2667.0', '15N_CPMG_50.0', '15N_CPMG_100.0', '15N_CPMG_150.0', '15N_CPMG_200.0', '15N_CPMG_250.0', '15N_CPMG_300.0', '15N_CPMG_350.0', '15N_CPMG_400.0', '15N_CPMG_500.0', '15N_CPMG_600.0', '15N_CPMG_700.0', '15N_CPMG_800.0', '15N_CPMG_900.0', '15N_CPMG_1000.0']] 
7590          ] 
7591          for name, value in data: 
7592              # Does it exist? 
7593              self.assert_(hasattr(cdp, name)) 
7594   
7595              # Check the object. 
7596              obj = getattr(cdp, name) 
7597              if not isinstance(data, dict): 
7598                  self.assertEqual(obj, value) 
7599   
7600              # Check the global dictionary data. 
7601              else: 
7602                  for id in ids: 
7603                      self.assertEqual(obj[id], value[id]) 
7604   
7605          # Check the spin data. 
7606          h_data = [ 
7607              [  67.0,  21.47924,   0.42958], 
7608              [ 133.0,  16.73898,   0.33478], 
7609              [ 267.0,   9.97357,   0.19947], 
7610              [ 400.0,   8.23877,   0.24737], 
7611              [ 533.0,   7.59290,   0.24263], 
7612              [ 667.0,   7.45843,   0.24165], 
7613              [ 800.0,   7.11222,   0.23915], 
7614              [ 933.0,   7.40880,   0.24129], 
7615              [1067.0,   6.55191,   0.16629], 
7616              [1600.0,   6.72177,   0.23637], 
7617              [2133.0,   7.09629,   0.23904], 
7618              [2667.0,   7.14675,   0.23940] 
7619          ] 
7620          for disp_point, value, error in h_data: 
7621              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7622              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff[id], value) 
7623              self.assertEqual(cdp.mol[0].res[0].spin[0].r2eff_err[id], error) 
7624          n_data = [ 
7625              [  50.0,  27.15767,   0.54315], 
7626              [ 100.0,  26.55781,   0.53116], 
7627              [ 150.0,  24.73462,   0.49469], 
7628              [ 200.0,  20.98617,   0.41972], 
7629              [ 250.0,  17.82442,   0.35649], 
7630              [ 300.0,  15.55352,   0.31107], 
7631              [ 350.0,  13.78958,   0.27579], 
7632              [ 400.0,  12.48334,   0.24967], 
7633              [ 500.0,  11.55724,   0.23114], 
7634              [ 600.0,  10.53874,   0.21077], 
7635              [ 700.0,  10.07395,   0.20148], 
7636              [ 800.0,   9.62952,   0.19259], 
7637              [ 900.0,   9.49994,   0.19000], 
7638              [1000.0,   8.71350,   0.17427] 
7639          ] 
7640          for disp_point, value, error in n_data: 
7641              id = 'sq_cpmg_500.00000000_0.000_%.3f' % disp_point 
7642              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff[id], value) 
7643              self.assertEqual(cdp.mol[0].res[0].spin[1].r2eff_err[id], error) 
7644   
7645   
7646 -    def test_r2eff_fit_fixed_time(self): 
7647          """Test the relaxation dispersion 'R2eff' model for fixed time data in the auto-analysis.""" 
7648   
7649          # Execute the script. 
7650          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r2eff_calc.py') 
7651   
7652   
7653 -    def test_read_r2eff(self): 
7654          """Test the reading of a file containing r2eff values.""" 
7655   
7656          # Create the sequence data, and name the spins. 
7657          self.interpreter.residue.create(1, 'Gly') 
7658          self.interpreter.residue.create(2, 'Gly') 
7659          self.interpreter.residue.create(3, 'Gly') 
7660   
7661          # Read the file. 
7662          self.interpreter.relax_data.read(ri_id='R2eff.600', ri_type='R2eff', frq=600*1e6, file='r2eff.out', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'r2eff', res_num_col=1, res_name_col=2, data_col=3, error_col=4) 
7663   
7664          # Test the data. 
7665          self.assertEqual(cdp.mol[0].res[0].spin[0].ri_data['R2eff.600'], 15.000) 
7666          self.assertEqual(cdp.mol[0].res[1].spin[0].ri_data['R2eff.600'], 4.2003) 
7667          self.assertEqual(cdp.mol[0].res[2].spin[0].ri_data['R2eff.600'], 7.2385) 
7668   
7669   
7670 -    def test_r20_from_min_r2eff_cpmg(self): 
7671          """Test speeding up grid search. Support requst sr #3151 U{https://gna.org/support/index.php?3151}. 
7672   
7673          User function to set the R20 parameters in the default grid search using the minimum R2eff value. 
7674   
7675          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7676          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7677   
7678          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7679          Data is for experiment at 25 degree Celcius. 
7680          """ 
7681   
7682          # Base data setup. 
7683          pipe_name = 'base pipe' 
7684          pipe_type = 'relax_disp' 
7685          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7686          select_spin_index = list(range(0, 1)) 
7687          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7688   
7689          # Generate r20 key. 
7690          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
7691          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
7692   
7693          ## Now prepare for MODEL calculation. 
7694          MODEL = "CR72" 
7695   
7696          # Change pipe. 
7697          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
7698          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7699          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7700   
7701          # Then select model. 
7702          self.interpreter.relax_disp.select_model(model=MODEL) 
7703   
7704          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
7705          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
7706   
7707          # Test result, for normal run. 
7708          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7709              # Get the spin_params. 
7710              spin_params = spin.params 
7711   
7712              # Defined fixed values for testing. 
7713              if spin_id == ":10@N": 
7714                  self.assertEqual(spin.r2[r20_key_600], 20.282732526087106) 
7715                  self.assertEqual(spin.r2[r20_key_500], 18.475299724356649) 
7716   
7717              # Print out. 
7718              print("r2_600=%2.2f r2_500=%2.2f spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin_id, resi, resn)) 
7719   
7720              # Testing the r2 values for the different fields are not the same. 
7721              self.assert_(spin.r2[r20_key_600] != spin.r2[r20_key_500]) 
7722   
7723              # Test values are larger than 0. 
7724              self.assert_(spin.r2[r20_key_600] > 0.0) 
7725              self.assert_(spin.r2[r20_key_500] > 0.0) 
7726   
7727              # Loop over the experiment settings. 
7728              r2eff_600 = [] 
7729              r2eff_500 = [] 
7730              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
7731                  # Create the data key. 
7732                  data_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
7733   
7734                  # Extract the r2 eff data. 
7735                  r2eff = spin.r2eff[data_key] 
7736                  if frq == 599.8908617*1E6: 
7737                      r2eff_600.append(r2eff) 
7738                  elif frq == 499.862139*1E6: 
7739                      r2eff_500.append(r2eff) 
7740   
7741              # Sort values. 
7742              r2eff_600.sort() 
7743              r2eff_500.sort() 
7744   
7745              # Test values again. 
7746              print("For r20 600MHz min r2eff=%3.3f."%(min(r2eff_600))) 
7747              print(r2eff_600) 
7748              self.assertEqual(spin.r2[r20_key_600], min(r2eff_600)) 
7749              print("") 
7750   
7751              print("For r20 500MHz min r2eff=%3.3f."%(min(r2eff_500))) 
7752              print(r2eff_500) 
7753              self.assertEqual(spin.r2[r20_key_500], min(r2eff_500)) 
7754              print("") 
7755   
7756          print("###########################################") 
7757          print("Trying GRID SEARCH for minimum R2eff values") 
7758   
7759          ### Test just the Grid search. 
7760          GRID_INC = 5 
7761   
7762          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7763   
7764          ### Then test the value.set function. 
7765          # Change pipe. 
7766          pipe_name_MODEL = "%s_%s_2"%(pipe_name, MODEL) 
7767          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
7768          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
7769   
7770          # Then select model. 
7771          self.interpreter.relax_disp.select_model(model=MODEL) 
7772   
7773          # Then set the standard parameter values. 
7774          for param in spin_params: 
7775              print("Setting standard parameter for param: %s"%param) 
7776              self.interpreter.value.set(param=param, index=None) 
7777   
7778          # Test result, for normal run. 
7779          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7780              # Print out. 
7781              print("r2_600=%2.2f r2_500=%2.2f pA=%2.2f, dw=%2.2f, kex=%2.2f, spin_id=%s resi=%i resn=%s"%(spin.r2[r20_key_600], spin.r2[r20_key_500], spin.pA, spin.dw, spin.kex, spin_id, resi, resn)) 
7782   
7783              # Testing the r2 values. 
7784              self.assertEqual(spin.r2[r20_key_600], 10.00) 
7785              self.assertEqual(spin.r2[r20_key_500], 10.00) 
7786              self.assertEqual(spin.pA, 0.9) 
7787              self.assertEqual(spin.dw, 1.0) 
7788              self.assertEqual(spin.kex, 1000.0) 
7789   
7790          print("###########################################") 
7791          print("Trying GRID SEARCH for standard R2eff values") 
7792   
7793          ### Test just the Grid search. 
7794          GRID_INC = 5 
7795   
7796          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
7797   
7798          ### Run auto_analysis. 
7799          # The grid search size (the number of increments per dimension). 
7800          GRID_INC = 5 
7801   
7802          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
7803          MC_NUM = 3 
7804   
7805          # Model selection technique. 
7806          MODSEL = 'AIC' 
7807   
7808          # Execute the auto-analysis (fast). 
7809          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
7810          OPT_FUNC_TOL = 1e-1 
7811          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
7812          OPT_MAX_ITERATIONS = 1000 
7813          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
7814   
7815          # Run the analysis. 
7816          relax_disp.Relax_disp(pipe_name=pipe_name_r2eff, results_dir=ds.tmpdir, models=[MODEL], grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL, set_grid_r20=True) 
7817   
7818   
7819 -    def test_show_apod_extract(self): 
7820          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7821   
7822          # The path to the data files. 
7823          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7824   
7825          # Define file name. 
7826          file_name = '128_0_FT.ft2' 
7827   
7828          # Call function. 
7829          get_output = show_apod_extract(file_name=file_name, dir=data_path) 
7830   
7831          # Define how output should look like. 
7832          # The output from showApod differs slightly according to NMRPipe version. But 'Noise Std Dev' is the same. 
7833          # Dont test lines which can differ. 
7834          show_apod_ver = [ 
7835              'REMARK Effect of Processing on Peak Parameters and Noise for %s'%(data_path+sep+file_name), 
7836              'REMARK Automated Noise Std Dev in Processed Data: 8583.41', 
7837              'REMARK Noise Std Dev Before Processing H1 and N15: 60.6558', 
7838              '', 
7839              'VARS   AXIS LABEL  TSIZE FSIZE LW_ADJ LW_FINAL HI_FACTOR VOL_FACTOR SIGMA_FACTOR', 
7840              'FORMAT %s   %-8s   %4d   %4d   %7.4f  %7.4f    %.4e      %.4e       %.4e'] 
7841              #'', 
7842              #'       X    H1       800  2048 0.8107 3.7310   4.9903e-03 9.8043e-04 5.2684e-02', 
7843              #'       Y    N15      128   256 0.7303 3.0331   3.1260e-02 7.8434e-03 1.3413e-01'] 
7844   
7845          for i, line in enumerate(show_apod_ver): 
7846              line_ver = get_output[i] 
7847   
7848              print(line) 
7849              if line[:50] == 'REMARK Noise Std Dev Before Processing H1 and N15:': 
7850                  continue 
7851              # Make the string test 
7852              self.assertEqual(line, line_ver) 
7853   
7854   
7855 -    def test_show_apod_rmsd(self): 
7856          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod.""" 
7857   
7858          # The path to the data files. 
7859          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7860   
7861          # Define file name. 
7862          file_name = '128_0_FT.ft2' 
7863   
7864          # Call function. 
7865          rmsd = show_apod_rmsd(file_name=file_name, dir=data_path) 
7866   
7867          # Assert. 
7868          self.assertEqual(rmsd, 8583.41) 
7869   
7870   
7871 -    def test_show_apod_rmsd_dir_to_files(self): 
7872          """Test searching for all NMRPipe spectrum files in dir, call showApod, and write to files.""" 
7873   
7874          # The path to the data files. 
7875          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7876   
7877          # Call function, and get all file names. 
7878          wfile_paths = show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=data_path, outdir=self.tmpdir) 
7879   
7880          # Loop over file_paths. 
7881          for wfile_path in wfile_paths: 
7882              # Open the file. 
7883              get_data = extract_data(file=wfile_path) 
7884   
7885              # Extract line 0, column 0. 
7886              test = float(get_data[0][0]) 
7887   
7888              # Assert. 
7889              self.assertEqual(test, 8583.41) 
7890   
7891   
7892 -    def test_show_apod_rmsd_to_file(self): 
7893          """Test getting the spectrum noise for spectrum fourier transformed with NMRPipe, and tool showApod, and write to file.""" 
7894   
7895          # The path to the data files. 
7896          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'repeated_analysis'+sep+'SOD1'+sep+'cpmg_disp_sod1d90a_060518'+sep+'cpmg_disp_sod1d90a_060518_normal.fid'+sep+'ft2_data' 
7897   
7898          # Define file name. 
7899          file_name = '128_0_FT.ft2' 
7900   
7901          # Call function, and get file name. 
7902          wfile_path = show_apod_rmsd_to_file(file_name=file_name, dir=data_path, outdir=self.tmpdir) 
7903   
7904          # Open the file. 
7905          get_data = extract_data(file=wfile_path) 
7906   
7907          # Extract line 0, column 0. 
7908          test = float(get_data[0][0]) 
7909   
7910          # Assert. 
7911          self.assertEqual(test, 8583.41) 
7912   
7913   
7914 -    def test_sod1wt_t25_bug_21954_order_error_analysis(self): 
7915          """Error analysis of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
7916   
7917          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
7918          'SOD1-WT' CPMG data to the CR72 dispersion model. 
7919   
7920          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
7921          Data is for experiment at 25 degree Celcius. 
7922   
7923          bug #21954 U{https://gna.org/bugs/index.php?21954}: Order of spectrum.error_analysis is important. 
7924          """ 
7925   
7926          # Base data setup. 
7927          pipe_name = 'base pipe' 
7928          pipe_type = 'relax_disp' 
7929          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
7930          select_spin_index = list(range(0, 1)) 
7931          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
7932   
7933          # Define replicated 
7934          repl_A = ['Z_A1', 'Z_A15'] 
7935          repl_B = ['Z_B1', 'Z_B18'] 
7936   
7937          # Loop over spectrum ID, and sort them 
7938          spectrum_ids_A = [] 
7939          spectrum_ids_B = [] 
7940          for spectrum_id in cdp.spectrum_ids: 
7941              if "A" in spectrum_id: 
7942                  spectrum_ids_A.append(spectrum_id) 
7943              elif "B" in spectrum_id: 
7944                  spectrum_ids_B.append(spectrum_id) 
7945   
7946          # To clean up old error analysis, delete attributes 
7947          delattr(cdp, "var_I") 
7948          delattr(cdp, "sigma_I") 
7949   
7950          # Perform error analysis 
7951          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7952          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7953   
7954          # Loop over spins, save errors to list 
7955          Errors_A_B = [] 
7956          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7957              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7958              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7959              Errors_A_B.append([A_err, B_err]) 
7960   
7961          # To clean up old error analysis, delete attributes 
7962          delattr(cdp, "var_I") 
7963          delattr(cdp, "sigma_I") 
7964   
7965          # Perform error analysis. Order is important 
7966          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_B) 
7967          self.interpreter.spectrum.error_analysis(subset=spectrum_ids_A) 
7968   
7969          # Loop over spins, save errors to list 
7970          Errors_B_A = [] 
7971          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
7972              A_err = spin.peak_intensity_err[spectrum_ids_A[0]] 
7973              B_err = spin.peak_intensity_err[spectrum_ids_B[0]] 
7974              Errors_B_A.append([A_err, B_err]) 
7975   
7976          # Make test for order of error 
7977          for i in range(len(Errors_A_B)): 
7978              Error_A_B = Errors_A_B[i] 
7979              Error_B_A = Errors_B_A[i] 
7980              self.assertAlmostEqual(Error_A_B[0], Error_B_A[0], 4) 
7981              self.assertAlmostEqual(Error_A_B[1], Error_B_A[1], 4) 
7982   
7983          # Make further tests for fixed values 
7984          std_A = math.sqrt((cdp.var_I[repl_A[0]] + cdp.var_I[repl_A[1]])/2) 
7985          std_A_fix = 2785.7263335738567 
7986   
7987          for id_A in spectrum_ids_A: 
7988              self.assertEqual(cdp.sigma_I[id_A], std_A) 
7989              self.assertAlmostEqual(cdp.sigma_I[id_A], std_A_fix, 7) 
7990   
7991          std_B = math.sqrt((cdp.var_I[repl_B[0]] + cdp.var_I[repl_B[1]])/2) 
7992          std_B_fix = 4967.3772030667988 
7993   
7994          for id_B in spectrum_ids_B: 
7995              self.assertEqual(cdp.sigma_I[id_B], std_B) 
7996              self.assertAlmostEqual(cdp.sigma_I[id_B], std_B_fix, 7) 
7997   
7998   
7999 -    def test_sod1wt_t25_to_cr72(self): 
8000          """Optimisation of SOD1-WT CPMG. From paper at U{http://dx.doi.org/10.1073/pnas.0907387106}. 
8001   
8002          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
8003          'SOD1-WT' CPMG data to the CR72 dispersion model. 
8004   
8005          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
8006          Data is for experiment at 25 degree Celcius. 
8007          """ 
8008   
8009          # Base data setup. 
8010          pipe_name = 'base pipe' 
8011          pipe_type = 'relax_disp' 
8012          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
8013          select_spin_index = list(range(0, 2)) 
8014          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
8015   
8016          # Generate r20 key. 
8017          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
8018          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
8019   
8020          ## Now prepare for MODEL calculation. 
8021          MODEL = "CR72" 
8022   
8023          # Change pipe. 
8024          pipe_name_MODEL = "%s_%s"%(pipe_name, MODEL) 
8025          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL) 
8026          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL) 
8027   
8028          # Then select model. 
8029          self.interpreter.relax_disp.select_model(model=MODEL) 
8030   
8031          # GRID inc of 7 was found to be appropriate not to find pA = 0.5. 
8032          GRID_INC = 7 
8033   
8034          # Store grid and minimisations results. 
8035          grid_results = [] 
8036          mini_results = [] 
8037          clust_results = [] 
8038   
8039          # Set the R20 parameters in the default grid search using the minimum R2eff value. 
8040          self.interpreter.relax_disp.r20_from_min_r2eff(force=False) 
8041   
8042          # Deselect insignificant spins. 
8043          self.interpreter.relax_disp.insignificance(level=1.0) 
8044   
8045          # Perform Grid Search. 
8046          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=GRID_INC, constraints=True, verbosity=1) 
8047   
8048          # Store result. 
8049          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8050              # Store grid results. 
8051              grid_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
8052   
8053          ## Now do minimisation. 
8054          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
8055          set_func_tol = 1e-9 
8056          set_max_iter = 100000 
8057          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
8058   
8059          # Store result. 
8060          pA_values = [] 
8061          kex_values = [] 
8062          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8063              # Store minimisation results. 
8064              mini_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
8065   
8066              # Store pA values. 
8067              pA_values.append(spin.pA) 
8068   
8069              # Store kex values. 
8070              kex_values.append(spin.kex) 
8071   
8072          print("\n# Now print before and after minimisation.\n") 
8073   
8074          # Print results. 
8075          for i in range(len(grid_results)): 
8076              # Get values. 
8077              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
8078              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
8079   
8080              print("GRID r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
8081              print("MIN  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
8082   
8083          ## Prepare for clustering 
8084          # Change pipe. 
8085          pipe_name_MODEL_CLUSTER = "%s_%s_Cluster"%(pipe_name, MODEL) 
8086          self.interpreter.pipe.copy(pipe_from=pipe_name_r2eff, pipe_to=pipe_name_MODEL_CLUSTER) 
8087          self.interpreter.pipe.switch(pipe_name=pipe_name_MODEL_CLUSTER) 
8088   
8089          # Then select model. 
8090          self.interpreter.relax_disp.select_model(model=MODEL) 
8091   
8092          # Define cluster id. 
8093          cluster_id = 'clust' 
8094   
8095          # Loop over spins to cluster them. 
8096          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8097              self.interpreter.relax_disp.cluster(cluster_id, spin_id) 
8098   
8099          # Copy over values. 
8100          self.interpreter.relax_disp.parameter_copy(pipe_from=pipe_name_MODEL, pipe_to=pipe_name_MODEL_CLUSTER) 
8101   
8102          # Test the median values is correct 
8103          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8104              print(pA_values) 
8105              # The the median pA value returned. 
8106              self.assertEqual(median(pA_values), spin.pA) 
8107   
8108              # The the median kex value returned. 
8109              self.assertEqual(median(kex_values), spin.kex) 
8110   
8111          ## Now do minimisation. 
8112          self.interpreter.minimise.execute(min_algor='simplex', func_tol=set_func_tol, max_iter=set_max_iter, constraints=True, scaling=True, verbosity=1) 
8113   
8114          # Store result. 
8115          for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
8116              # Store clust results. 
8117              clust_results.append([spin.r2[r20_key_600], spin.r2[r20_key_500], spin.dw, spin.pA, spin.kex, spin.chi2, spin_id, resi, resn]) 
8118   
8119              # Store the outcome of the clustering minimisation. 
8120              clust_pA = spin.pA 
8121              clust_kex = spin.kex 
8122   
8123          print("\n# Now testing.\n") 
8124   
8125          # Define results 
8126          test_res = {} 
8127          test_res[':10@N'] = {} 
8128          test_res[':10@N']['r2600'] = 18.429755324773360 
8129          test_res[':10@N']['r2500'] = 16.981349161968630 
8130          test_res[':10@N']['dw'] = 2.700755859433969 
8131          test_res[':10@N']['pA'] = 0.971531659288657 
8132          test_res[':10@N']['kex'] = 3831.766337047963134 
8133          test_res[':11@N'] = {} 
8134          test_res[':11@N']['r2600'] = 18.193409421115213 
8135          test_res[':11@N']['r2500'] = 17.308838135567765 
8136          test_res[':11@N']['dw'] = 2.706650302761793 
8137          test_res[':11@N']['pA'] = 0.971531659288657 
8138          test_res[':11@N']['kex'] = 3831.766337047963134 
8139   
8140          # Then make tests. 
8141          for i in range(len(grid_results)): 
8142              # Get values. 
8143              g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn = grid_results[i] 
8144              m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn = mini_results[i] 
8145              c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn = clust_results[i] 
8146   
8147              print("%s GRID   r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(g_spin_id, g_r2_600, g_r2_500, g_dw, g_pA, g_kex, g_chi2, g_spin_id, g_resi, g_resn)) 
8148              print("%s MIN    r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, m_r2_600, m_r2_500, m_dw, m_pA, m_kex, m_chi2, m_spin_id, m_resi, m_resn)) 
8149              print("%s Clust  r2600=%2.2f r2500=%2.2f dw=%1.1f pA=%1.3f kex=%3.2f chi2=%3.2f spin_id=%s resi=%i resn=%s"%(m_spin_id, c_r2_600, c_r2_500, c_dw, c_pA, c_kex, c_chi2, c_spin_id, c_resi, c_resn)) 
8150   
8151              # Make tests. 
8152              self.assertEqual(clust_pA, c_pA) 
8153              self.assertEqual(clust_kex, c_kex) 
8154   
8155              # Test values. 
8156              if c_spin_id in test_res: 
8157                  self.assertAlmostEqual(c_r2_600, test_res[c_spin_id]['r2600'], 4) 
8158                  self.assertAlmostEqual(c_r2_500, test_res[c_spin_id]['r2500'], 4) 
8159                  self.assertAlmostEqual(c_dw, test_res[c_spin_id]['dw'], 3) 
8160                  self.assertAlmostEqual(c_pA, test_res[c_spin_id]['pA'], 5) 
8161                  self.assertAlmostEqual(c_kex, test_res[c_spin_id]['kex'], 1) 
8162   
8163          # Save disp graph to temp. 
8164          #self.interpreter.relax_disp.plot_disp_curves(dir="~"+sep+"test", num_points=1000, extend=500.0, force=True). 
8165   
8166   
8167 -    def test_sod1wt_t25_to_sherekhan_input(self): 
8168          """Conversion of SOD1-WT CPMG R2eff values into input files for sherekhan. 
8169   
8170          Optimisation of Kaare Teilum, Melanie H. Smith, Eike Schulz, Lea C. Christensen, Gleb Solomentseva, Mikael Oliveberg, and Mikael Akkea 2009 
8171          'SOD1-WT' CPMG data to the CR72 dispersion model. 
8172   
8173          This uses the data from paper at U{http://dx.doi.org/10.1073/pnas.0907387106}.  This is CPMG data with a fixed relaxation time period recorded at fields of 500 and 600MHz. 
8174          Data is for experiment at 25 degree Celcius. 
8175          """ 
8176   
8177          # Base data setup. 
8178          pipe_name = 'base pipe' 
8179          pipe_type = 'relax_disp' 
8180          pipe_name_r2eff = "%s_R2eff"%(pipe_name) 
8181          select_spin_index = list(range(0, 2)) 
8182          self.setup_sod1wt_t25(pipe_name=pipe_name, pipe_type=pipe_type, pipe_name_r2eff=pipe_name_r2eff, select_spin_index=select_spin_index) 
8183   
8184          # Generate r20 key. 
8185          r20_key_600 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=599.8908617*1E6) 
8186          r20_key_500 = generate_r20_key(exp_type=EXP_TYPE_CPMG_SQ, frq=499.862139*1E6) 
8187   
8188          # Cluster everything, to analyse together. 
8189          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":1-1000") 
8190   
8191          # Write input 
8192          self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=ds.tmpdir) 
8193   
8194          # Check the r2eff set files. 
8195          print("\nChecking the R2eff input set files.") 
8196          files = [[ds.tmpdir + sep + 'cluster1', 'sherekhan_frq1.in'], [ ds.tmpdir + sep + 'cluster1', 'sherekhan_frq2.in']] 
8197   
8198          # First check file exists 
8199          for dir, file in files: 
8200              print(dir+sep+file) 
8201              self.assert_(access(dir+sep+file, F_OK)) 
8202   
8203          # Define how files should look like 
8204          data_set_600 = [ 
8205               "60.8272464287\n", 
8206               "0.06\n", 
8207               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
8208               "# G10\n", 
8209               "              33.333       26.53556078711      0.5236104771163\n", 
8210               "              66.667       25.29735243318        0.48766574122\n", 
8211               "                 100       25.09470361403      0.4820438864671\n", 
8212               "             133.333       25.15603274331      0.4837377286085\n", 
8213               "             166.667       24.27213341753      0.4599457904395\n", 
8214               "                 200       24.00364120328      0.4529773198905\n", 
8215               "             266.667       24.03511395168      0.4537880662536\n", 
8216               "                 300       23.04761040024      0.4291039120557\n", 
8217               "             333.333       22.95530300787      0.4268745963972\n", 
8218               "                 400       23.06158810662      0.4294426293624\n", 
8219               "             466.667       22.26799054092      0.4106809618644\n", 
8220               "             533.333       21.99851418823      0.4045232104735\n", 
8221               "             666.667       21.19651570955      0.3868136173831\n", 
8222               "             833.333       20.30938498379      0.3682604887899\n", 
8223               "                1000       20.28273252609       0.367719392568\n", 
8224               "# D11\n", 
8225               "              33.333       24.76520269878      0.5026475808706\n", 
8226               "              66.667        24.8773107448      0.5058752916906\n", 
8227               "                 100       24.90357815239      0.5066348551479\n", 
8228               "             133.333        23.7782506151      0.4751950583865\n", 
8229               "             166.667       23.68548762076      0.4727017128631\n", 
8230               "                 200       23.58629651618      0.4700517377679\n", 
8231               "             266.667       23.47734671187      0.4671601744044\n", 
8232               "                 300       24.08647493772      0.4835855560598\n", 
8233               "             333.333       22.98314371029      0.4542918950801\n", 
8234               "                 400       22.80339361568      0.4497107885587\n", 
8235               "             466.667       22.91634335366      0.4525833037874\n", 
8236               "             533.333       22.59774140046      0.4445334311324\n", 
8237               "             666.667        20.9177750759      0.4046955726046\n", 
8238               "             833.333       20.71792550566      0.4002363835007\n", 
8239               "                1000       19.54080006349      0.3751112751853\n", 
8240          ] 
8241   
8242          # Check data_set_600 
8243          file = open(files[0][0]+sep+files[0][1]) 
8244          lines = file.readlines() 
8245          file.close() 
8246          self.assertEqual(len(data_set_600), len(lines)) 
8247          for i in range(len(data_set_600)): 
8248              # Make the string test 
8249              self.assertEqual(data_set_600[i], lines[i]) 
8250   
8251          # Define how files should look like 
8252          data_set_500 = [ 
8253               "50.6846152368\n", 
8254               "0.04\n", 
8255               "# nu_cpmg (Hz)       R2eff (rad/s)        Error               \n", 
8256               "# G10\n", 
8257               "                  50       22.28084307393      0.2944966344183\n", 
8258               "                 100       21.93494977761      0.2910362768307\n", 
8259               "                 150       21.09850032232       0.282892238351\n", 
8260               "                 200       20.86493960397      0.2806737853646\n", 
8261               "                 250       20.75287269752      0.2796178205016\n", 
8262               "                 300       20.25597152406      0.2750013546989\n", 
8263               "                 350       19.92172163467      0.2719555756504\n", 
8264               "                 400       19.97712052922       0.272457105051\n", 
8265               "                 450       19.46807010415      0.2678972122793\n", 
8266               "                 500       19.76875460947      0.2705774849203\n", 
8267               "                 550       19.39161367402      0.2672216964327\n", 
8268               "                 600       19.03949517697      0.2641417899694\n", 
8269               "                 650       19.12218812132      0.2648605059901\n", 
8270               "                 700       19.01037461457      0.2638893584683\n", 
8271               "                 800       18.83395162904      0.2623674321143\n", 
8272               "                 900       18.47529972436      0.2593123604687\n", 
8273               "                1000        18.5252023121      0.2597343394038\n", 
8274               "# D11\n", 
8275               "                  50       22.15403890237      0.3285588379827\n", 
8276               "                 100       21.80946781746      0.3247185598713\n", 
8277               "                 150       21.77715415505       0.324361526682\n", 
8278               "                 200       21.41647464235      0.3204122024881\n", 
8279               "                 250       21.17099940822      0.3177616325958\n", 
8280               "                 300       21.03740030577      0.3163316496664\n", 
8281               "                 350       20.95393648281      0.3154427665172\n", 
8282               "                 400       20.93311399332       0.315221543436\n", 
8283               "                 450       20.18219905222      0.3073848655291\n", 
8284               "                 500       19.93599065085      0.3048744697057\n", 
8285               "                 550       19.68475725452      0.3023424499113\n", 
8286               "                 600       19.33575433934      0.2988741928798\n", 
8287               "                 650       19.53915692194      0.3008886196853\n", 
8288               "                 700        19.2018754351      0.2975587767134\n", 
8289               "                 800       18.82360965368      0.2938866923878\n", 
8290               "                 900       18.71861761238      0.2928790380131\n", 
8291               "                1000       17.95878049287      0.2857341721151\n", 
8292          ] 
8293   
8294          # Check data_set_500 
8295          file = open(files[1][0]+sep+files[1][1]) 
8296          lines = file.readlines() 
8297          file.close() 
8298          self.assertEqual(len(data_set_500), len(lines)) 
8299          for i in range(len(data_set_500)): 
8300              # Make the string test 
8301              self.assertEqual(data_set_500[i], lines[i]) 
8302   
8303          # Test local dir tests. This will be turned off in system test. 
8304          turn_on_local_dir_test = False 
8305   
8306          if turn_on_local_dir_test: 
8307              ## Now check to local folder with None argument. 
8308              # Write input 
8309              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None) 
8310   
8311              # Check the r2eff set files. 
8312              print("\nChecking the R2eff input set files.") 
8313              files = [[path.join(getcwd(), 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), 'cluster1'), 'sherekhan_frq2.in']] 
8314   
8315              # First check file exists 
8316              for dir, file in files: 
8317                  print(dir+sep+file) 
8318                  self.assert_(access(dir+sep+file, F_OK)) 
8319   
8320              ## Now check to local folder with dir argument. 
8321              # Write input 
8322              set_dir = "Test_ShereKhan" 
8323              self.interpreter.relax_disp.sherekhan_input(force=True, spin_id=None, dir=set_dir) 
8324   
8325              # Check the r2eff set files. 
8326              print("\nChecking the R2eff input set files.") 
8327              files = [[path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq1.in'], [path.join(getcwd(), set_dir, 'cluster1'), 'sherekhan_frq2.in']] 
8328   
8329              # First check file exists 
8330              for dir, file in files: 
8331                  print(dir+sep+file) 
8332                  self.assert_(access(dir+sep+file, F_OK)) 
8333   
8334   
8335 -    def test_sprangers_data_to_mmq_cr72(self, model=None): 
8336          """Test the 'MMQ CR72' model fitting against Remco Sprangers' ClpP data. 
8337   
8338          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MMQ CPMG data with a fixed relaxation time period. 
8339          """ 
8340   
8341          # Reset. 
8342          self.interpreter.reset() 
8343   
8344          # Create the data pipe and load the base data. 
8345          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8346          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8347   
8348          # The model data pipe. 
8349          model = 'MMQ CR72' 
8350          pipe_name = "%s - relax_disp" % model 
8351          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8352          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8353   
8354          # Set the model. 
8355          self.interpreter.relax_disp.select_model(model=model) 
8356   
8357          # Cluster everything. 
8358          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8359   
8360          # Copy the data. 
8361          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8362   
8363          # Alias the spins. 
8364          spin135S = cdp.mol[0].res[0].spin[0] 
8365          spin135F = cdp.mol[0].res[0].spin[1] 
8366          spin137S = cdp.mol[0].res[1].spin[0] 
8367          spin137F = cdp.mol[0].res[1].spin[1] 
8368   
8369          # The R20 keys. 
8370          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=600e6) 
8371          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8372   
8373          # Set the cluster specific parameters (only for the first spin). 
8374          spin135S.pA = 0.836591763632 
8375          spin135S.kex = 241.806525261 
8376   
8377          # Set the initial parameter values. 
8378          spin135S.r2 = {r20_key1: 28.2493431552, r20_key2: 31.7517334715} 
8379          spin135S.dw = 0.583003118785 
8380          spin135S.dwH = 0.0361441944301 
8381   
8382          spin135F.r2 = {r20_key1: 42.7201839991, r20_key2: 57.3178617389} 
8383          spin135F.dw = 0.805849745104 
8384          spin135F.dwH = 0.0215791945715 
8385   
8386          spin137S.r2 = {r20_key1: 26.0134115256, r20_key2: 30.575806934} 
8387          spin137S.dw = 0.688107568372 
8388          spin137S.dwH = 0.0344463604043 
8389   
8390          spin137F.r2 = {r20_key1: 46.6969397337, r20_key2: 58.602384101} 
8391          spin137F.dw = 0.94978299907 
8392          spin137F.dwH = 1.4818877939e-07 
8393   
8394          # Low precision optimisation. 
8395          self.interpreter.minimise.execute(min_algor='simplex', func_tol=1e-10, max_iter=1000) 
8396   
8397          # Printout. 
8398          print("\n\nOptimised parameters:\n") 
8399          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8400          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8401          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8402          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8403          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8404          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8405          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8406          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8407          print("\n        # Set the cluster specific parameters (only for the first spin).") 
8408          print("        spin135S.pA = %s" % spin135S.pA) 
8409          print("        spin135S.kex = %s" % spin135S.kex) 
8410          print("\n        # Set the initial parameter values.") 
8411          print("        spin135S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135S.r2[r20_key1], spin135S.r2[r20_key2])) 
8412          print("        spin135S.dw = %s" % spin135S.dw) 
8413          print("        spin135S.dwH = %s" % spin135S.dwH) 
8414          print("\n        spin135F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin135F.r2[r20_key1], spin135F.r2[r20_key2])) 
8415          print("        spin135F.dw = %s" % spin135F.dw) 
8416          print("        spin135F.dwH = %s" % spin135F.dwH) 
8417          print("\n        spin137S.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137S.r2[r20_key1], spin137S.r2[r20_key2])) 
8418          print("        spin137S.dw = %s" % spin137S.dw) 
8419          print("        spin137S.dwH = %s" % spin137S.dwH) 
8420          print("\n        spin137F.r2 = {r20_key1: %s, r20_key2: %s}" % (spin137F.r2[r20_key1], spin137F.r2[r20_key2])) 
8421          print("        spin137F.dw = %s" % spin137F.dw) 
8422          print("        spin137F.dwH = %s" % spin137F.dwH) 
8423   
8424          # Checks for residue :135S. 
8425          self.assertAlmostEqual(spin135S.r2[r20_key1], 28.2493445347425, 4) 
8426          self.assertAlmostEqual(spin135S.r2[r20_key2], 31.7517352342937, 4) 
8427          self.assertAlmostEqual(spin135S.pA, 0.836591714049569, 4) 
8428          self.assertAlmostEqual(spin135S.dw, 0.583003004605869, 4) 
8429          self.assertAlmostEqual(spin135S.dwH, 0.0361441894065963, 4) 
8430          self.assertAlmostEqual(spin135S.kex/100, 241.806464344233/100, 4) 
8431          self.assertAlmostEqual(spin135S.chi2, 12.4224060116473, 4) 
8432   
8433          # Checks for residue :135F. 
8434          self.assertAlmostEqual(spin135F.r2[r20_key1], 42.7201844426839, 4) 
8435          self.assertAlmostEqual(spin135F.r2[r20_key2], 57.3178718548898, 4) 
8436          self.assertAlmostEqual(spin135F.pA, 0.836591714049569, 4) 
8437          self.assertAlmostEqual(spin135F.dw, 0.805849748711916, 4) 
8438          self.assertAlmostEqual(spin135F.dwH, 0.0215791669142752, 4) 
8439          self.assertAlmostEqual(spin135F.kex/100, 241.806464344233/100, 4) 
8440          self.assertAlmostEqual(spin135F.chi2, 12.4224060116473, 4) 
8441   
8442          # Checks for residue :137S. 
8443          self.assertAlmostEqual(spin137S.r2[r20_key1], 26.013412509919, 4) 
8444          self.assertAlmostEqual(spin137S.r2[r20_key2], 30.5758092335097, 4) 
8445          self.assertAlmostEqual(spin137S.pA, 0.836591714049569, 4) 
8446          self.assertAlmostEqual(spin137S.dw, 0.688107406812537, 4) 
8447          self.assertAlmostEqual(spin137S.dwH, 0.034446357344577, 4) 
8448          self.assertAlmostEqual(spin137S.kex/100, 241.806464344233/100, 4) 
8449          self.assertAlmostEqual(spin137S.chi2, 12.4224060116473, 4) 
8450   
8451          # Checks for residue :137F. 
8452          self.assertAlmostEqual(spin137F.r2[r20_key1], 46.696935090697, 4) 
8453          self.assertAlmostEqual(spin137F.r2[r20_key2], 58.6023842513446, 4) 
8454          self.assertAlmostEqual(spin137F.pA, 0.836591714049569, 4) 
8455          self.assertAlmostEqual(spin137F.dw, 0.94978325541294, 4) 
8456          self.assertAlmostEqual(spin137F.dwH, 1.5189362257653e-07, 4) 
8457          self.assertAlmostEqual(spin137F.kex/100, 241.806464344233/100, 4) 
8458          self.assertAlmostEqual(spin137F.chi2, 12.4224060116473, 4) 
8459   
8460   
8461 -    def test_sprangers_data_to_ns_mmq_2site(self, model=None): 
8462          """Test the 'NS MMQ 2-site' model fitting against Remco Sprangers' ClpP data. 
8463   
8464          This uses the data from Remco Sprangers' paper at http://dx.doi.org/10.1073/pnas.0507370102.  This is MQ CPMG data with a fixed relaxation time period. 
8465          """ 
8466   
8467          # Reset. 
8468          self.interpreter.reset() 
8469   
8470          # Create the data pipe and load the base data. 
8471          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Sprangers_ClpP' 
8472          self.interpreter.state.load(data_path+sep+'r2eff_values') 
8473   
8474          # The model data pipe. 
8475          model = 'NS MMQ 2-site' 
8476          pipe_name = "%s - relax_disp" % model 
8477          self.interpreter.pipe.copy(pipe_from='base pipe', pipe_to=pipe_name, bundle_to='relax_disp') 
8478          self.interpreter.pipe.switch(pipe_name=pipe_name) 
8479   
8480          # Set the model. 
8481          self.interpreter.relax_disp.select_model(model=model) 
8482   
8483          # Cluster everything. 
8484          self.interpreter.relax_disp.cluster(cluster_id='all', spin_id=":135-137") 
8485   
8486          # Copy the data. 
8487          self.interpreter.value.copy(pipe_from='R2eff', pipe_to=pipe_name, param='r2eff') 
8488   
8489          # Alias the spins. 
8490          spin135S = cdp.mol[0].res[0].spin[0] 
8491          spin135F = cdp.mol[0].res[0].spin[1] 
8492          spin137S = cdp.mol[0].res[1].spin[0] 
8493          spin137F = cdp.mol[0].res[1].spin[1] 
8494   
8495          # The R20 keys. 
8496          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8497          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_CPMG_MQ, frq=800e6) 
8498   
8499          # Set the cluster specific parameters (only for the first spin). 
8500          spin135S.pA = 0.847378444499757 
8501          spin135S.kex = 264.055604934724329 
8502   
8503          # Set the initial parameter values. 
8504          spin135S.r2 = {r20_key1: 30.315119723745390, r20_key2: 37.411874745645299} 
8505          spin135S.dw = 0.585574008745351 
8506          spin135S.dwH = 0.000000000000002 
8507   
8508          spin135F.r2 = {r20_key1: 41.440843383778287, r20_key2: 56.989726795397893} 
8509          spin135F.dw = 0.856699277665748 
8510          spin135F.dwH = 0.000000000582587 
8511   
8512          spin137S.r2 = {r20_key1: 23.051695938570266, r20_key2: 28.352806483953824} 
8513          spin137S.dw = 0.772904450844973 
8514          spin137S.dwH = 0.183351478512970 
8515   
8516          spin137F.r2 = {r20_key1: 44.702032074210429, r20_key2: 56.453146052685319} 
8517          spin137F.dw = 0.984568590342831 
8518          spin137F.dwH = 0.000000001993458 
8519   
8520          # Low precision optimisation. 
8521          self.interpreter.minimise.execute(min_algor='simplex', line_search=None, hessian_mod=None, hessian_type=None, func_tol=1e-5, grad_tol=None, max_iter=100, constraints=True, scaling=True, verbosity=1) 
8522   
8523          # Printout. 
8524          print("\n\nOptimised parameters:\n") 
8525          print("%-20s %-20s %-20s %-20s %-20s" % ("Parameter", "Value (:135@S)", "Value (:135@F)", "Value (:137@S)", "Value (:137@F)")) 
8526          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (500 MHz)", spin135S.r2[r20_key1], spin135F.r2[r20_key1], spin137S.r2[r20_key1], spin137F.r2[r20_key1])) 
8527          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("R2 (800 MHz)", spin135S.r2[r20_key2], spin135F.r2[r20_key2], spin137S.r2[r20_key2], spin137F.r2[r20_key2])) 
8528          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("pA", spin135S.pA, spin135F.pA, spin137S.pA, spin137F.pA)) 
8529          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dw", spin135S.dw, spin135F.dw, spin137S.dw, spin137F.dw)) 
8530          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("dwH", spin135S.dwH, spin135F.dwH, spin137S.dwH, spin137F.dwH)) 
8531          print("%-20s %20.15g %20.15g %20.15g %20.15g" % ("kex", spin135S.kex, spin135F.kex, spin137S.kex, spin137F.kex)) 
8532          print("%-20s %20.15g %20.15g %20.15g %20.15g\n" % ("chi2", spin135S.chi2, spin135F.chi2, spin137S.chi2, spin137F.chi2)) 
8533   
8534          # FIXME: Remove this temporary return and properly check the results. 
8535          return 
8536   
8537          # Checks for residue :135S. 
8538          self.assertAlmostEqual(spin135S.r2[r20_key1], 30.3151197237454, 4) 
8539          self.assertAlmostEqual(spin135S.r2[r20_key2], 37.4118747456453, 4) 
8540          self.assertAlmostEqual(spin135S.pA, 0.847378444499757, 4) 
8541          self.assertAlmostEqual(spin135S.dw, 0.585574008745351, 4) 
8542          self.assertAlmostEqual(spin135S.dwH, 2e-15, 4) 
8543          self.assertAlmostEqual(spin135S.kex, 264.055604934724, 4) 
8544          self.assertAlmostEqual(spin135S.chi2, 13.859423588071, 1) 
8545   
8546          # Checks for residue :135F. 
8547          self.assertAlmostEqual(spin135F.r2[r20_key1], 41.4408433837783, 4) 
8548          self.assertAlmostEqual(spin135F.r2[r20_key2], 56.9897267953979, 4) 
8549          self.assertAlmostEqual(spin135F.pA, 0.847378444499757, 4) 
8550          self.assertAlmostEqual(spin135F.dw, 0.856699277665748, 4) 
8551          self.assertAlmostEqual(spin135F.dwH, 5.82587e-10, 4) 
8552          self.assertAlmostEqual(spin135F.kex, 264.055604934724, 4) 
8553          self.assertAlmostEqual(spin135F.chi2, 13.859423588071, 1) 
8554   
8555          # Checks for residue :137S. 
8556          self.assertAlmostEqual(spin137S.r2[r20_key1], 23.0516959385703, 4) 
8557          self.assertAlmostEqual(spin137S.r2[r20_key2], 28.3528064839538, 4) 
8558          self.assertAlmostEqual(spin137S.pA, 0.847378444499757, 4) 
8559          self.assertAlmostEqual(spin137S.dw, 0.772904450844973, 4) 
8560          self.assertAlmostEqual(spin137S.dwH, 0.18335147851297, 4) 
8561          self.assertAlmostEqual(spin137S.kex, 264.055604934724, 4) 
8562          self.assertAlmostEqual(spin137S.chi2, 13.859423588071, 1) 
8563   
8564          # Checks for residue :137F. 
8565          self.assertAlmostEqual(spin137F.r2[r20_key1], 44.7020320742104, 4) 
8566          self.assertAlmostEqual(spin137F.r2[r20_key2], 56.4531460526853, 4) 
8567          self.assertAlmostEqual(spin137F.pA, 0.847378444499757, 4) 
8568          self.assertAlmostEqual(spin137F.dw, 0.984568590342831, 4) 
8569          self.assertAlmostEqual(spin137F.dwH, 2.0931309e-09, 4) 
8570          self.assertAlmostEqual(spin137F.kex, 264.055604934724, 4) 
8571          self.assertAlmostEqual(spin137F.chi2, 13.859423588071, 1) 
8572   
8573   
8574 -    def test_tp02_data_to_ns_r1rho_2site(self, model=None): 
8575          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data.""" 
8576   
8577          # Setup the data. 
8578          self.setup_tp02_data_to_ns_r1rho_2site() 
8579   
8580          # Alias the spins. 
8581          spin1 = cdp.mol[0].res[0].spin[0] 
8582          spin2 = cdp.mol[0].res[1].spin[0] 
8583   
8584          # The R20 keys. 
8585          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8586          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8587   
8588          # Checks for residue :1. 
8589          self.assertAlmostEqual(spin1.r2[r20_key1], 8.50207717367548, 4) 
8590          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4680429589972, 4) 
8591          self.assertAlmostEqual(spin1.pA, 0.864523128842393, 4) 
8592          self.assertAlmostEqual(spin1.dw, 8.85204828994151, 4) 
8593          self.assertAlmostEqual(spin1.kex/1000, 1199.56359549637/1000, 4) 
8594          self.assertAlmostEqual(spin1.chi2, 2.99182130153514, 4) 
8595   
8596          # Checks for residue :2. 
8597          self.assertAlmostEqual(spin2.r2[r20_key1], 10.2099357790203, 4) 
8598          self.assertAlmostEqual(spin2.r2[r20_key2], 16.2137648697873, 4) 
8599          self.assertAlmostEqual(spin2.pA, 0.836488681031685, 4) 
8600          self.assertAlmostEqual(spin2.dw, 9.5505714779503, 4) 
8601          self.assertAlmostEqual(spin2.kex/1000, 1454.45726998929/1000, 4) 
8602          self.assertAlmostEqual(spin2.chi2, 0.000402231563481261, 4) 
8603   
8604   
8605 -    def test_tp02_data_to_ns_r1rho_2site_cluster(self, model=None): 
8606          """Test the relaxation dispersion 'NS R1rho 2-site' model fitting against the 'TP02' test data, when performing clustering.""" 
8607   
8608          # Setup the data. 
8609          self.setup_tp02_data_to_ns_r1rho_2site(clustering=True) 
8610   
8611          # Alias the spins. 
8612          spin1 = cdp.mol[0].res[0].spin[0] 
8613          spin2 = cdp.mol[0].res[1].spin[0] 
8614   
8615          # The R20 keys. 
8616          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8617          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8618   
8619          # Checks for residue :1. 
8620          self.assertAlmostEqual(spin1.r2[r20_key1], 8.48607207881462, 4) 
8621          self.assertAlmostEqual(spin1.r2[r20_key2], 13.4527609061722, 4) 
8622          self.assertAlmostEqual(spin1.pA, 0.863093838784425, 4) 
8623          self.assertAlmostEqual(spin1.dw, 8.86218096536618, 4) 
8624          self.assertAlmostEqual(spin1.kex/1000, 1186.22749648299/1000, 4) 
8625          self.assertAlmostEqual(spin1.chi2, 3.09500996065247, 4) 
8626   
8627          # Checks for residue :2. 
8628          self.assertAlmostEqual(spin2.r2[r20_key1], 10.4577906018883, 4) 
8629          self.assertAlmostEqual(spin2.r2[r20_key2], 16.4455550953792, 4) 
8630          self.assertAlmostEqual(spin2.pA, 0.863093838784425, 4) 
8631          self.assertAlmostEqual(spin2.dw, 11.5841168862587, 4) 
8632          self.assertAlmostEqual(spin2.kex/1000, 1186.22749648299/1000, 4) 
8633          self.assertAlmostEqual(spin2.chi2, 3.09500996065247, 4) 
8634   
8635   
8636 -    def test_tp02_data_to_mp05(self): 
8637          """Test the dispersion 'MP05' model fitting against the 'TP02' test data.""" 
8638   
8639          # Fixed time variable and the models. 
8640          ds.fixed = True 
8641          ds.models = ['R2eff', 'MP05'] 
8642   
8643          # Execute the script. 
8644          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8645   
8646          # Switch back to the data pipe for the optimisation. 
8647          self.interpreter.pipe.switch('MP05 - relax_disp') 
8648   
8649          # The equivalent MP05 parameters. 
8650          r1rho_prime = [[10.0058086343329, 15.005806870124], [12.0766320470785, 18.0767503536277]] 
8651          pA = [0.775055484521586, 0.500000000036595] 
8652          kex = [1235.20361276079, 2378.31403454691] 
8653          delta_omega = [7.08194146569694, 5.4083562844306] 
8654          chi2 = [0.0370400968727768, 0.182141732163934] 
8655   
8656          # Alias the spins. 
8657          spin1 = cdp.mol[0].res[0].spin[0] 
8658          spin2 = cdp.mol[0].res[1].spin[0] 
8659   
8660          # The R20 keys. 
8661          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8662          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8663   
8664          # Printout. 
8665          print("\n\nOptimised parameters:\n") 
8666          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8667          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8668          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8669          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8670          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8671          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8672          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8673   
8674          # Check each spin. 
8675          spin_index = 0 
8676          for spin, spin_id in spin_loop(return_id=True): 
8677              # Printout. 
8678              print("\nSpin %s." % spin_id) 
8679   
8680              # Check the fitted parameters. 
8681              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8682              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8683              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8684              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8685              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8686              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8687   
8688              # Increment the spin index. 
8689              spin_index += 1 
8690   
8691   
8692 -    def test_tp02_data_to_tap03(self): 
8693          """Test the dispersion 'TAP03' model fitting against the 'TP02' test data.""" 
8694   
8695          # Fixed time variable and the models. 
8696          ds.fixed = True 
8697          ds.models = ['R2eff', 'TAP03'] 
8698   
8699          # Execute the script. 
8700          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8701   
8702          # Switch back to the data pipe for the optimisation. 
8703          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8704   
8705          # The equivalent TAP03 parameters. 
8706          r1rho_prime = [[10.0058156589442, 15.005818505006], [12.0766046472748, 18.076648462452]] 
8707          pA = [0.775042569092891, 0.500000000229685] 
8708          kex = [1235.20852748765, 2379.47085580169] 
8709          delta_omega = [7.08176806468445, 5.40708372863538] 
8710          chi2 = [0.0371366837083293, 0.182212857256044] 
8711   
8712          # Alias the spins. 
8713          spin1 = cdp.mol[0].res[0].spin[0] 
8714          spin2 = cdp.mol[0].res[1].spin[0] 
8715   
8716          # The R20 keys. 
8717          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8718          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8719   
8720          # Printout. 
8721          print("\n\nOptimised parameters:\n") 
8722          print("%-20s %-20s %-20s" % ("Parameter", "Value (:1)", "Value (:2)")) 
8723          print("%-20s %20.15g %20.15g" % ("R2 (500 MHz)", spin1.r2[r20_key1], spin2.r2[r20_key1])) 
8724          print("%-20s %20.15g %20.15g" % ("R2 (800 MHz)", spin1.r2[r20_key2], spin2.r2[r20_key2])) 
8725          print("%-20s %20.15g %20.15g" % ("pA", spin1.pA, spin2.pA)) 
8726          print("%-20s %20.15g %20.15g" % ("dw", spin1.dw, spin2.dw)) 
8727          print("%-20s %20.15g %20.15g" % ("kex", spin1.kex, spin2.kex)) 
8728          print("%-20s %20.15g %20.15g\n" % ("chi2", spin1.chi2, spin2.chi2)) 
8729   
8730          # Switch to the 'MP05' model data pipe, then check for each spin. 
8731          self.interpreter.pipe.switch('TAP03 - relax_disp') 
8732          spin_index = 0 
8733          for spin, spin_id in spin_loop(return_id=True): 
8734              # Printout. 
8735              print("\nSpin %s." % spin_id) 
8736   
8737              # Check the fitted parameters. 
8738              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8739              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8740              self.assertAlmostEqual(spin.pA, pA[spin_index], 3) 
8741              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8742              self.assertAlmostEqual(spin.kex/1000.0, kex[spin_index]/1000.0, 3) 
8743              self.assertAlmostEqual(spin.chi2, chi2[spin_index], 3) 
8744   
8745              # Increment the spin index. 
8746              spin_index += 1 
8747   
8748   
8749 -    def test_task_7882_monte_carlo_std_residual(self): 
8750          """Implementation of Task #7882 U{https://gna.org/task/?7882}: Implement Monte-Carlo simulation, where errors are generated with width of standard deviation or residuals""" 
8751   
8752          # First check that results are stored with minimisation, to make sure that Sum of Squares are stored (Chi2 without weighting) and degrees of freedom (dof) is stored. 
8753   
8754          # Load the results file from a clustered minimisation. 
8755          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'error_testing'+sep+'task_7882' 
8756          self.interpreter.results.read(file_name) 
8757   
8758          # Get the spins, which was used for clustering. 
8759          spins_cluster = cdp.clustering['sel'] 
8760          spins_free = cdp.clustering['free spins'] 
8761   
8762          # For sanity check, calculate degree of freedom. 
8763          cur_spin_id = spins_cluster[0] 
8764          cur_spin = return_spin(cur_spin_id) 
8765   
8766          # Calculate total number of datapoins. 
8767          N = len(spins_cluster) 
8768          N_dp = N * len(cur_spin.r2eff) 
8769   
8770          # Calculate number of paramaters. For CR72, there is R2 per spectrometer field, individual dw, and shared kex and pA. 
8771          N_par = cdp.spectrometer_frq_count * N + N + 1 + 1 
8772          dof = N_dp - N_par 
8773   
8774          # Sanity check of parameters. 
8775          print(N_par, N_dp) 
8776   
8777          # Number of MC 
8778          mc_nr = 3 
8779   
8780          # Setup MC for errors generated from the distribution described by chi2 and degrees of freedom from best fit. 
8781          self.interpreter.monte_carlo.setup(number=mc_nr) 
8782   
8783          # Create data. 
8784          self.interpreter.monte_carlo.create_data(distribution="red_chi2") 
8785   
8786          # Setup MC again. 
8787          self.interpreter.monte_carlo.setup(number=mc_nr) 
8788   
8789          # Create data, and set the fixed error value, without setting the correct distribution. 
8790          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, fixed_error=1.) 
8791   
8792          # Setup MC again. 
8793          self.interpreter.monte_carlo.setup(number=mc_nr) 
8794   
8795          # Create data, with fixed error distribution, but not setting the error value. 
8796          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, distribution="fixed") 
8797   
8798          # Setup MC again. 
8799          self.interpreter.monte_carlo.create_data(distribution="fixed", fixed_error=1.) 
8800   
8801          # Now select the R2eff model, and try again. Expect raising an error. 
8802          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
8803   
8804          # Setup MC again. 
8805          self.interpreter.monte_carlo.setup(number=mc_nr) 
8806   
8807          # Create data, and assert failure. 
8808          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, distribution="red_chi2") 
8809          self.assertRaises(RelaxError, self.interpreter.monte_carlo.create_data, method="direct", distribution="red_chi2") 
8810   
8811   
8812 -    def x_test_task_7882_kex_conf(self): 
8813          """Test related to Task #7882 U{https://gna.org/task/?7882}: Try making a confidence interval of kex. 
8814          According to the regression book of Graphpad: U{http://www.graphpad.com/faq/file/Prism4RegressionBook.pdf}. 
8815          Page 109-111. 
8816          """ 
8817   
8818          # Load the results file from a clustered minimisation. 
8819          file_name = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'error_testing'+sep+'task_7882' 
8820          self.interpreter.results.read(file_name) 
8821   
8822          # Get the spins, which was used for clustering. 
8823          spins_cluster = cdp.clustering['sel'] 
8824          spins_free = cdp.clustering['free spins'] 
8825   
8826          # For sanity check, calculate degree of freedom. 
8827          cur_spin_id = spins_cluster[0] 
8828          cur_spin = return_spin(cur_spin_id) 
8829   
8830          # Calculate total number of datapoins. 
8831          Ns = len(spins_cluster) 
8832          N_dp = Ns * len(cur_spin.r2eff) 
8833   
8834          # Calculate number of paramaters. For CR72, there is R2 per spectrometer field, individual dw, and shared kex and pA. 
8835          N_par = cdp.spectrometer_frq_count * Ns + Ns + 1 + 1 
8836          dof_fit = N_dp - N_par 
8837   
8838          # Assert values. 
8839          self.assertEqual(Ns, 61) 
8840          self.assertEqual(N_dp, 1952) 
8841          self.assertEqual(N_par, 185) 
8842   
8843          # Confidence interval of kex. 
8844          # The number of parameters to check is kex = 1. 
8845          P = 1 
8846          # Number of datapoints 
8847          N = N_dp 
8848          # The degrees of freedom for this confidence interval 
8849          dof_conf = N - P 
8850   
8851          # The critical value of the F distribution with p-value of 0.05 for 95% confidence. 
8852          # Can be calculated with microsoft excel: 
8853          # F=FINV(0,05; P; dof_conf), F=FINV(0,05; P; dof_conf), F=FINV(0,05; 1; 1951)=3,846229551 
8854          # Can also be calculated with: import scipy.stats; scipy.stats.f.isf(0.05, 1, 1951)=3.8462295505435562 
8855          F = 3.8462295505435562 
8856          # Then calculate the scaling of chi2, which is the weighted sum of squares of best fit. 
8857          scale = F*P/dof_conf +1 
8858   
8859          # Get the sum of best fit. 
8860          SSbest_fit = cur_spin.chi2 
8861          SSbest_kex = cur_spin.kex 
8862   
8863          # Get the scaled sum of best fit 
8864          SSall_fixed = SSbest_fit * scale 
8865   
8866          print(SSbest_fit, scale, SSall_fixed) 
8867   
8868          # Now generate a list of kex values to try. 
8869          kex_cur = cur_spin.kex 
8870          kex_list = linspace(kex_cur - 1500, kex_cur + 3000, 200) 
8871   
8872          chi2_list = [] 
8873   
8874          for kex in kex_list: 
8875              self.interpreter.value.set(val=kex, param='kex') 
8876   
8877              # Calculate the chi2 values. 
8878              self.interpreter.minimise.calculate(verbosity=0) 
8879   
8880              # Get the chi2 value 
8881              chi2_cur = cur_spin.chi2 
8882              print("kex=%3.2f, chi2=%3.2f"%(kex, chi2_cur), chi2_cur<SSall_fixed) 
8883   
8884              # Add to list 
8885              chi2_list.append(chi2_cur) 
8886   
8887          # Now make to numpy array. 
8888          chi2_list = asarray(chi2_list) 
8889   
8890          # Now make a selection mask based on the criteria. 
8891          sel_mask = chi2_list < SSall_fixed 
8892   
8893          # Select values of kex, and chi2_list 
8894          kex_sel = kex_list[sel_mask] 
8895          chi2_sel = chi2_list[sel_mask] 
8896   
8897          # Now make plot 
8898          print(SSbest_kex, SSbest_fit, SSall_fixed) 
8899          print(kex_sel) 
8900          print(chi2_sel) 
8901   
8902          if True: 
8903              import matplotlib.pyplot as plt 
8904   
8905              plt.plot(kex_sel, chi2_sel, "bo") 
8906              plt.plot(SSbest_kex, SSbest_fit, "g*") 
8907              plt.show() 
8908   
8909   
8910 -    def test_tp02_data_to_tp02(self): 
8911          """Test the relaxation dispersion 'TP02' model curve fitting to fixed time synthetic data.""" 
8912   
8913          # Fixed time variable. 
8914          ds.fixed = True 
8915   
8916          # Execute the script. 
8917          self.interpreter.run(script_file=status.install_path + sep+'test_suite'+sep+'system_tests'+sep+'scripts'+sep+'relax_disp'+sep+'r1rho_off_res_tp02.py') 
8918   
8919          # The original parameters. 
8920          r1rho_prime = [[10.0, 15.0], [12.0, 18.0]] 
8921          pA = 0.7654321 
8922          kex = 1234.56789 
8923          delta_omega = [7.0, 9.0] 
8924   
8925          # The R20 keys. 
8926          r20_key1 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=500e6) 
8927          r20_key2 = generate_r20_key(exp_type=EXP_TYPE_R1RHO, frq=800e6) 
8928   
8929          # Switch to the 'TP02' model data pipe, then check for each spin. 
8930          self.interpreter.pipe.switch('TP02 - relax_disp') 
8931          spin_index = 0 
8932          for spin, spin_id in spin_loop(return_id=True): 
8933              # Printout. 
8934              print("\nSpin %s." % spin_id) 
8935   
8936              # Check the fitted parameters. 
8937              self.assertAlmostEqual(spin.r2[r20_key1]/10, r1rho_prime[spin_index][0]/10, 4) 
8938              self.assertAlmostEqual(spin.r2[r20_key2]/10, r1rho_prime[spin_index][1]/10, 4) 
8939              self.assertAlmostEqual(spin.dw, delta_omega[spin_index], 3) 
8940              self.assertAlmostEqual(spin.kex/1000.0, kex/1000.0, 3) 
8941   
8942              # Increment the spin index. 
8943              spin_index += 1 
8944   
8945   
8946 -    def test_value_write_calc_rotating_frame_params_int(self): 
8947          """System test of the value.write function to write intensities for an R1rho setup. 
8948          This system test is to make sure, that modifying the API for special parameters theta and w_eff does not alter the functionality value.write. 
8949   
8950          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8951          """ 
8952   
8953          # Load the state. 
8954          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
8955          self.interpreter.state.load(statefile, force=True) 
8956   
8957          # Set filepaths. 
8958          int_filepath = ds.tmpdir+sep+'int.out' 
8959   
8960          # Write out the intensity parameter file. 
8961          # The writing out of intensity file is to make sure the API function retains its function after modification for special parameters. 
8962          self.interpreter.value.write(param='peak_intensity', file='int.out', dir=ds.tmpdir, scaling=1.0, force=True) 
8963   
8964          # Test the file exists. 
8965          self.assert_(access(int_filepath, F_OK)) 
8966   
8967          # Open the files for testing. 
8968          int_file = open(int_filepath, 'r') 
8969   
8970          # Loop over the intensity file to test values. 
8971          for line in int_file: 
8972              # Skip lines starting with #. 
8973              if line[0] == "#": 
8974                  continue 
8975   
8976              # Split the line 
8977              linesplit = line.split() 
8978   
8979              # Assume values 
8980              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
8981                  self.assertEqual(linesplit[5], "115571.4") 
8982              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
8983                  self.assertEqual(linesplit[5], "68377.52") 
8984              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
8985                  self.assertEqual(linesplit[5], "9141.689") 
8986              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
8987                  self.assertEqual(linesplit[5], "29123.77") 
8988              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
8989                  self.assertEqual(linesplit[5], "58914.94") 
8990   
8991          # Close files 
8992          int_file.close() 
8993   
8994   
8995 -    def test_value_write_calc_rotating_frame_params_theta(self): 
8996          """System test of the value.write function to write return values of theta from calc_rotating_frame_params() function for an R1rho setup. 
8997   
8998          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
8999          """ 
9000   
9001          # Load the state. 
9002          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
9003          self.interpreter.state.load(statefile, force=True) 
9004   
9005          # Set filepaths. 
9006          theta_filepath = ds.tmpdir+sep+'theta.out' 
9007   
9008          # Write out the theta parameter file. 
9009          self.interpreter.value.write(param='theta', file='theta.out', dir=ds.tmpdir, scaling=1.0, force=True) 
9010   
9011          # Test the file exists. 
9012          self.assert_(access(theta_filepath, F_OK)) 
9013   
9014          # Open the files for testing. 
9015          theta_file = open(theta_filepath, 'r') 
9016   
9017          # Loop over the theta file to test values. 
9018          for line in theta_file: 
9019              # Skip lines starting with #. 
9020              if line[0] == "#": 
9021                  continue 
9022              # Print lines, not including newline character. 
9023              print(line[:-1]) 
9024   
9025              # Split the line 
9026              linesplit = line.split() 
9027   
9028              # Assume values 
9029              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
9030                  self.assertNotEqual(linesplit[5], "None") 
9031              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
9032                  self.assertNotEqual(linesplit[5], "None") 
9033              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
9034                  self.assertNotEqual(linesplit[5], "None") 
9035              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
9036                  self.assertNotEqual(linesplit[5], "None") 
9037              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
9038                  self.assertNotEqual(linesplit[5], "None") 
9039   
9040          # Close files 
9041          theta_file.close() 
9042   
9043   
9044 -    def test_value_write_calc_rotating_frame_params_w_eff(self): 
9045          """System test of the value.write function to write return values of w_eff from calc_rotating_frame_params() function for an R1rho setup. 
9046   
9047          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
9048          """ 
9049   
9050          # Load the state. 
9051          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2' 
9052          self.interpreter.state.load(statefile, force=True) 
9053   
9054          # Set filepaths. 
9055          w_eff_filepath = ds.tmpdir+sep+'w_eff.out' 
9056   
9057          # Write out the w_eff parameter file. 
9058          self.interpreter.value.write(param='w_eff', file='w_eff.out', dir=ds.tmpdir, scaling=1.0, force=True) 
9059   
9060          # Test the file exists. 
9061          self.assert_(access(w_eff_filepath, F_OK)) 
9062   
9063          # Open the files for testing. 
9064          w_eff_file = open(w_eff_filepath, 'r') 
9065   
9066          # Loop over the w_eff file to test values. 
9067          for line in w_eff_file: 
9068              # Skip lines starting with #. 
9069              if line[0] == "#": 
9070                  continue 
9071              # Print lines, not including newline character. 
9072              print(line[:-1]) 
9073   
9074              # Split the line 
9075              linesplit = line.split() 
9076   
9077              # Assume values 
9078              if linesplit[0] == "None" and linesplit[1] == "5" and linesplit[2] == "I": 
9079                  self.assertNotEqual(linesplit[5], "None") 
9080              elif linesplit[0] == "None" and linesplit[1] == "6" and linesplit[2] == "S": 
9081                  self.assertNotEqual(linesplit[5], "None") 
9082              elif linesplit[0] == "None" and linesplit[1] == "8" and linesplit[2] == "S": 
9083                  self.assertNotEqual(linesplit[5], "None") 
9084              elif linesplit[0] == "None" and linesplit[1] == "9" and linesplit[2] == "A": 
9085                  self.assertNotEqual(linesplit[5], "None") 
9086              elif linesplit[0] == "None" and linesplit[1] == "10" and linesplit[2] == "L": 
9087                  self.assertNotEqual(linesplit[5], "None") 
9088   
9089          # Close files 
9090          w_eff_file.close() 
9091   
9092   
9093 -    def test_value_write_calc_rotating_frame_params_auto_analysis(self): 
9094          """System test of the auto_analysis value.write function to write theta and w_eff values for an R1rho setup. 
9095   
9096          This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}. 
9097          """ 
9098   
9099          # Load the state. 
9100          statefile = status.install_path+sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344.bz2' 
9101          self.interpreter.state.load(statefile, force=True) 
9102   
9103          # Set pipe name, bundle and type. 
9104          pipe_name = 'base pipe' 
9105          pipe_bundle = 'relax_disp' 
9106          pipe_type = 'relax_disp' 
9107   
9108          # The path to the data files. 
9109          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013' 
9110   
9111          # Deselect all spins 
9112          self.interpreter.deselect.all() 
9113   
9114          # Specify spins to be selected. 
9115          select_spin_ids = [ 
9116          ":13@N", 
9117          ":15@N", 
9118          ":16@N", 
9119          ":25@N", 
9120          ":26@N", 
9121          ":28@N", 
9122          ":39@N", 
9123          ":40@N", 
9124          ":41@N", 
9125          ":43@N", 
9126          ":44@N", 
9127          ":45@N", 
9128          ":49@N", 
9129          ":52@N", 
9130          ":53@N"] 
9131   
9132          # Reverse the selection for the spins. 
9133          for curspin in select_spin_ids: 
9134              print("Selecting spin %s"%curspin) 
9135              self.interpreter.deselect.reverse(spin_id=curspin) 
9136   
9137          # Read the R1 data 
9138          self.interpreter.relax_data.read(ri_id='R1', ri_type='R1', frq=cdp.spectrometer_frq_list[0], file='R1_fitted_values.txt', dir=data_path, mol_name_col=1, res_num_col=2, res_name_col=3, spin_num_col=4, spin_name_col=5, data_col=6, error_col=7) 
9139   
9140          # The dispersion models. 
9141          MODELS = ['R2eff'] 
9142   
9143          # The grid search size (the number of increments per dimension). 
9144          GRID_INC = 4 
9145   
9146          # The number of Monte Carlo simulations to be used for error analysis at the end of the analysis. 
9147          MC_NUM = 3 
9148   
9149          # Model selection technique. 
9150          MODSEL = 'AIC' 
9151   
9152          # Execute the auto-analysis (fast). 
9153          # Standard parameters are: func_tol = 1e-25, grad_tol = None, max_iter = 10000000, 
9154          OPT_FUNC_TOL = 1e-1 
9155          relax_disp.Relax_disp.opt_func_tol = OPT_FUNC_TOL 
9156          OPT_MAX_ITERATIONS = 1000 
9157          relax_disp.Relax_disp.opt_max_iterations = OPT_MAX_ITERATIONS 
9158   
9159          # Run the analysis. 
9160          relax_disp.Relax_disp(pipe_name=pipe_name, pipe_bundle=pipe_bundle, results_dir=ds.tmpdir, models=MODELS, grid_inc=GRID_INC, mc_sim_num=MC_NUM, modsel=MODSEL) 
9161   
9162          ## Check for file creation 
9163          # Set filepaths. 
9164          theta_filepath = ds.tmpdir+sep+MODELS[0]+sep+'theta.out' 
9165          w_eff_filepath = ds.tmpdir+sep+MODELS[0]+sep+'w_eff.out' 
9166   
9167          # Test the files exists. 
9168          self.assert_(access(theta_filepath, F_OK)) 
9169          self.assert_(access(w_eff_filepath, F_OK)) 
9170   
9171          # Open the files for testing. 
9172          theta_file = open(theta_filepath, 'r') 
9173          theta_result = [ 
9174              "# Parameter description:  Rotating frame tilt angle : ( theta = arctan(w_1 / Omega) ) (rad).\n", 
9175              "#\n", 
9176              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
9177              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9178              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9179              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9180              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9181              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9182              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9183              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9184              "None          13         L           None        N                1.83827367612531                   None                                           1.79015307643158                   None                                            2.2768687598681                  None                                          2.08461171779445                  None                                          2.00120623474388                  None                                          1.92825070277699                  None                                          1.47212860033516                   None                                           1.12978017906854                   None                                           1.20415336139956                   None                                          0.901691390796334                  None                                         0.687390207543568                   None                                          0.455635480573046                  None                                         0.281637123971289                   None                                          0.138259661766539                   None                                       \n", 
9185              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9186              "None          15         R           None        N                1.58367544790673                   None                                           1.58127411936947                   None                                           1.61085209029811                  None                                          1.59731540507347                  None                                          1.59237108385522                  None                                          1.58834866344307                  None                                           1.2251048782537                   None                                          0.938142786712004                   None                                           1.03297495592991                   None                                          0.683284686224254                  None                                         0.594447788256641                   None                                          0.383528609383686                  None                                         0.262780814059893                   None                                          0.133469839450564                   None                                       \n", 
9187              "None          16         T           None        N                1.40984232256624                   None                                           1.43947245672073                   None                                           1.10299856647417                  None                                          1.24811470332083                  None                                          1.30521602599932                  None                                          1.35302443831853                  None                                          1.07923777467974                   None                                          0.833345927788896                   None                                          0.934350308974616                   None                                          0.581325254389991                  None                                         0.543659670184793                   None                                          0.346238480454282                  None                                         0.251454336191817                   None                                          0.130436714663781                   None                                       \n", 
9188              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9189              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9190              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9191              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9192              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9193              "None          25         Q           None        N                1.81569700258844                   None                                           1.77137827615015                   None                                           2.23175875585624                  None                                          2.04612705363098                  None                                           1.9673155780155                  None                                          1.89908711012298                  None                                          1.44829660124856                   None                                           1.11023386429581                   None                                           1.18716091371256                   None                                          0.877306975624962                  None                                         0.677790118853413                   None                                          0.447932002242236                  None                                         0.279785379050945                   None                                          0.137802891887767                   None                                       \n", 
9194              "None          26         Q           None        N                1.61128821168674                   None                                           1.60374392042003                   None                                           1.69619923953765                  None                                          1.65403989292986                  None                                          1.63856717205868                  None                                          1.62595755714564                  None                                          1.24977859227795                   None                                          0.956353494917591                   None                                           1.04972090035774                   None                                          0.702164059520172                  None                                         0.603227813742091                   None                                          0.390116910781037                  None                                         0.264658552037535                   None                                          0.133960994297096                   None                                       \n", 
9195              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9196              "None          28         Q           None        N                1.65182797011356                   None                                           1.63676707684161                   None                                           1.81830827892972                  None                                           1.7365089711986                  None                                          1.70601955220877                  None                                          1.68102938663686                  None                                          1.28685736157369                   None                                          0.984047498595701                   None                                            1.0749792109454                   None                                          0.731585685663053                  None                                         0.616577997665602                   None                                          0.400219205533665                  None                                         0.267471993812649                   None                                          0.134690869499646                   None                                       \n", 
9197              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9198              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9199              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9200              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9201              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9202              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9203              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9204              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9205              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9206              "None          39         L           None        N                1.76426439181176                   None                                           1.72885318885161                   None                                           2.11826300085737                  None                                          1.95430201082222                  None                                          1.88794717058464                  None                                          1.83172922971397                  None                                          1.39549951193417                   None                                           1.06783946148624                   None                                           1.14997013232702                   None                                          0.826128785942585                  None                                         0.657105386950171                   None                                          0.431542911580536                  None                                         0.275725736430539                   None                                          0.136791385554619                   None                                       \n", 
9207              "None          40         M           None        N                 1.5521741199158                   None                                           1.55564594516135                   None                                           1.51290906497298                  None                                          1.53245929150759                  None                                          1.53960430408466                  None                                          1.54541832596591                  None                                          1.19750223001929                   None                                          0.917959090226757                   None                                           1.01428385962747                   None                                          0.662779584695967                  None                                         0.584708929219264                   None                                          0.376271266885303                  None                                         0.260671619214194                   None                                          0.132914250767089                   None                                       \n", 
9208              "None          41         A           None        N                1.68339451828261                   None                                           1.66252964414082                   None                                           1.90911961276946                  None                                          1.79959323497326                  None                                          1.75801925517113                  None                                          1.72370710837265                  None                                          1.31646868936419                   None                                           1.00647189763597                   None                                           1.09525348649914                   None                                           0.75605702767542                  None                                         0.627395557358039                   None                                          0.408481831044309                  None                                         0.269716174238842                   None                                          0.135267948387412                   None                                       \n", 
9209              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9210              "None          43         F           None        N                1.58506597154432                   None                                           1.58240542750303                   None                                           1.61517196062351                  None                                          1.60017740004898                  None                                          1.59469990835425                  None                                          1.59024353162528                  None                                          1.22633651794829                   None                                          0.939047922181951                   None                                           1.03380990731605                   None                                          0.684214484755514                  None                                         0.594884298549546                   None                                          0.383855128702894                  None                                         0.262874695048502                   None                                           0.13349447283116                   None                                       \n", 
9211              "None          44         I           None        N                1.57575471961837                   None                                           1.57483015671791                   None                                           1.58622388390755                  None                                          1.58100758841935                  None                                          1.57910319967536                  None                                          1.57755415552211                  None                                          1.21811077066835                   None                                          0.933010299763027                   None                                           1.02823520295828                   None                                           0.67802911457195                  None                                         0.591972285081647                   None                                          0.381678892926696                  None                                         0.262247347241724                   None                                          0.133329708422379                   None                                       \n", 
9212              "None          45         K           None        N                1.77147501495754                   None                                           1.73479633022489                   None                                           2.13509660780385                  None                                          1.96751045408372                  None                                          1.89924480319914                  None                                          1.84124387452692                  None                                          1.40277881643715                   None                                           1.07361367582571                   None                                           1.15506365550891                   None                                          0.832963505534767                  None                                         0.659913187081268                   None                                          0.433751178249555                  None                                         0.276282572106685                   None                                           0.13693095791902                   None                                       \n", 
9213              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9214              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9215              "None          49         A           None        N                2.00297059962685                   None                                           1.92978318052058                   None                                           2.53305709323468                  None                                          2.33052197276846                  None                                          2.22870514722639                  None                                          2.13201782446864                  None                                           1.6587904412969                   None                                           1.29333162369472                   None                                           1.34311052758116                   None                                           1.12559033900783                  None                                         0.770195063841652                   None                                          0.524846264860003                  None                                         0.296857751274362                   None                                          0.141908833673671                   None                                       \n", 
9216              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9217              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9218              "None          52         V           None        N                1.82421571143794                   None                                           1.77845404105203                   None                                           2.24910726268822                  None                                          2.06078232916932                  None                                          1.98017451806059                  None                                          1.91012195713554                  None                                          1.45724107606646                   None                                           1.11753869321304                   None                                           1.19352234944057                   None                                          0.886361068343012                  None                                         0.681372607920812                   None                                          0.450799407357501                  None                                         0.280478735779163                   None                                          0.137974257665877                   None                                       \n", 
9219              "None          53         A           None        N                2.05019708195234                   None                                           1.97089957318506                   None                                           2.58789168363698                  None                                          2.39027806684801                  None                                          2.28731354878582                  None                                           2.1872118539319                  None                                           1.7165709935896                   None                                           1.34832362477229                   None                                           1.38879751095815                   None                                            1.2085314357749                  None                                         0.799450059125864                   None                                          0.550583841461621                  None                                          0.30195492609136                   None                                          0.143090604877102                   None                                       \n", 
9220              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9221              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9222              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9223              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9224              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
9225          ] 
9226          # Check the created theta file. 
9227          lines = theta_file.readlines() 
9228          for i in range(len(lines)): 
9229              # Test lines starting with # 
9230              if theta_result[i][0] == "#": 
9231                  self.assertEqual(theta_result[i], lines[i]) 
9232              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
9233              if theta_result[i] == lines[i]: 
9234                  self.assertEqual(theta_result[i], lines[i]) 
9235              # If the line is not equal each other, make a slower comparison of values. 
9236              else: 
9237                  # Print lines if they don't match. To help find differences. 
9238                  print(theta_result[i]) 
9239                  print(lines[i]) 
9240   
9241                  # First test first 62 characters containing spin information 
9242                  self.assertEqual(theta_result[i][:62], lines[i][:62]) 
9243   
9244                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
9245                  theta_result_s = theta_result[i][62:].split()[::2] 
9246                  print(theta_result_s ) 
9247                  lines_s = lines[i][62:].split()[::2] 
9248                  print(lines_s) 
9249                  # Loop over the value elements 
9250                  for j in range(len(lines_s)): 
9251                      print(theta_result_s[j], lines_s[j]) 
9252                      # Assume a precision to digits. 
9253                      self.assertAlmostEqual(float(theta_result_s[j]), float(lines_s[j]), 14) 
9254   
9255          # Close file 
9256          theta_file.close() 
9257   
9258          w_eff_file = open(w_eff_filepath, 'r') 
9259          w_eff_result = [ 
9260              "# Parameter description:  Effective field in rotating frame : ( w_eff = sqrt(Omega^2 + w_1^2) ) (rad.s^-1).\n", 
9261              "#\n", 
9262              "# mol_name    res_num    res_name    spin_num    spin_name    r1rho_799.77739910_118.078_1341.110    sd(r1rho_799.77739910_118.078_1341.110)    r1rho_799.77739910_118.078_1648.500    sd(r1rho_799.77739910_118.078_1648.500)    r1rho_799.77739910_118.078_431.000    sd(r1rho_799.77739910_118.078_431.000)    r1rho_799.77739910_118.078_651.200    sd(r1rho_799.77739910_118.078_651.200)    r1rho_799.77739910_118.078_800.500    sd(r1rho_799.77739910_118.078_800.500)    r1rho_799.77739910_118.078_984.000    sd(r1rho_799.77739910_118.078_984.000)    r1rho_799.77739910_124.247_1341.110    sd(r1rho_799.77739910_124.247_1341.110)    r1rho_799.77739910_130.416_1341.110    sd(r1rho_799.77739910_130.416_1341.110)    r1rho_799.77739910_130.416_1648.500    sd(r1rho_799.77739910_130.416_1648.500)    r1rho_799.77739910_130.416_800.500    sd(r1rho_799.77739910_130.416_800.500)    r1rho_799.77739910_142.754_1341.110    sd(r1rho_799.77739910_142.754_1341.110)    r1rho_799.77739910_142.754_800.500    sd(r1rho_799.77739910_142.754_800.500)    r1rho_799.77739910_179.768_1341.110    sd(r1rho_799.77739910_179.768_1341.110)    r1rho_799.77739910_241.459_1341.110    sd(r1rho_799.77739910_241.459_1341.110)    \n", 
9263              "None          5          I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9264              "None          6          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9265              "None          8          S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9266              "None          9          A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9267              "None          10         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9268              "None          11         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9269              "None          12         D           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9270              "None          13         L           None        N                8737.12883908829                   None                                           10612.1226552258                   None                                           3558.93734069587                  None                                          4698.27194621826                  None                                          5534.46153956037                  None                                          6599.82570817753                  None                                          8467.62674839481                   None                                           9318.00441649087                   None                                           11095.2662520767                   None                                           6412.33580591254                  None                                          13279.9803044242                   None                                            11430.254637056                  None                                          30318.7268264644                   None                                           61141.1080046448                   None                                       \n", 
9271              "None          14         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9272              "None          15         R           None        N                8427.14155005377                   None                                           10358.3995676635                   None                                           2710.22680763322                  None                                          4093.04942975722                  None                                          5030.86065069262                  None                                          6183.60685459024                  None                                          8956.28403254202                   None                                           10448.6627754369                   None                                           12060.4428066937                   None                                           7966.64282975241                  None                                          15045.8392092364                   None                                           13441.3586252373                  None                                          32438.4764809909                   None                                           63321.5201471181                   None                                       \n", 
9273              "None          16         T           None        N                 8536.7818857229                   None                                            10447.792678989                   None                                           3034.01707453628                  None                                           4314.2767521567                  None                                          5212.43600885913                  None                                          6332.21319855067                  None                                          9558.14311447582                   None                                           11384.2336494604                   None                                           12879.4604966293                   None                                           9159.34604475399                  None                                          16290.1746838959                   None                                           14821.0200530829                  None                                          33866.5933527757                   None                                           64785.3205696403                   None                                       \n", 
9274              "None          17         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9275              "None          18         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9276              "None          19         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9277              "None          21         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9278              "None          24         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9279              "None          25         Q           None        N                8685.60895531182                   None                                           10569.7459677762                   None                                           3430.51272680396                  None                                          4601.75421490393                  None                                          5452.76508815826                  None                                          6531.46859076009                  None                                          8490.06475886501                   None                                           9406.58372902508                   None                                           11169.7602637607                   None                                           6540.38696356753                  None                                          13437.7348017798                   None                                           11613.1632549021                  None                                          30514.0741594726                   None                                           61342.4792156782                   None                                       \n", 
9280              "None          26         Q           None        N                8433.35533683544                   None                                           10363.4554631194                   None                                           2729.48656005151                  None                                          4105.82770792005                  None                                          5041.26238350827                  None                                          6192.07245313098                  None                                          8880.08366342131                   None                                           10312.6868786802                   None                                           11942.8320576165                   None                                           7787.44854491812                  None                                          14853.4987024375                   None                                           13225.7048162038                  None                                          32213.6690023282                   None                                           63090.7407990801                   None                                       \n", 
9281              "None          27         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9282              "None          28         Q           None        N                8454.18308422202                   None                                           10380.4112885894                   None                                           2793.17494362899                  None                                          4148.43953208179                  None                                          5076.02756135055                  None                                          6220.40920270029                  None                                          8777.91538040813                   None                                           10118.8737706315                   None                                           11775.8792998529                   None                                           7528.90766101027                  None                                          14572.4015102398                   None                                            12909.211050939                  None                                          31882.8171856889                   None                                           62750.9120842199                   None                                       \n", 
9283              "None          29         V           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9284              "None          30         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9285              "None          31         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9286              "None          32         I           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9287              "None          33         L           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9288              "None          34         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9289              "None          35         S           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9290              "None          36         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9291              "None          38         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9292              "None          39         L           None        N                 8586.6405431352                   None                                           10488.5710521378                   None                                           3171.59430904777                  None                                          4412.11227722123                  None                                          5293.69814015286                  None                                          6399.27143075725                  None                                          8557.58926327909                   None                                           9617.45773774313                   None                                           11347.9169998729                   None                                           6840.20010813426                  None                                          13795.1250622375                   None                                           12024.9041436853                  None                                           30951.651485352                   None                                           61793.2130509111                   None                                       \n", 
9293              "None          40         M           None        N                8427.90394711227                   None                                           10359.0198301036                   None                                           2712.59646573568                  None                                          4094.61889210019                  None                                          5032.13762965554                  None                                           6184.6458240746                  None                                          9049.68452800053                   None                                           10607.7913029633                   None                                           12198.5639821231                   None                                           8174.23271685285                  None                                          15266.4924700447                   None                                           13687.9010998756                  None                                          32694.9043143038                   None                                           63584.6371927381                   None                                       \n", 
9294              "None          41         A           None        N                8480.14299737436                   None                                           10401.5648897003                   None                                           2870.79081440785                  None                                          4201.09083283266                  None                                          5119.14733505123                  None                                          6255.64579267482                  None                                          8706.50768957471                   None                                           9972.71017314947                   None                                           11650.5225246067                   None                                           7331.28858930568                  None                                          14354.1616183112                   None                                           12662.3378547029                  None                                          31623.9195264738                   None                                           62484.8290612112                   None                                       \n", 
9295              "None          42         A           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9296              "None          43         F           None        N                8427.30062786474                   None                                           10358.5289868368                   None                                            2710.7214015056                  None                                          4093.37694357637                  None                                          5031.12711571215                  None                                          6183.82364721878                  None                                          8952.31975962078                   None                                           10441.7375680915                   None                                           12054.4435931163                   None                                           7957.55789315654                  None                                          15036.1316712316                   None                                           13430.4914212645                  None                                          32427.1596037519                   None                                           63309.9050677925                   None                                       \n", 
9297              "None          44         I           None        N                8426.54623319716                   None                                           10357.9152496503                   None                                            2708.3751705368                  None                                          4091.82359712664                  None                                          5029.86337809029                  None                                          6182.79552045043                  None                                          8979.12144335458                   None                                           10488.2688526334                   None                                           12094.7720286018                   None                                           8018.51779989075                  None                                          15101.1843990883                   None                                           13503.2816173444                  None                                          32502.9389163062                   None                                           63387.6763306952                   None                                       \n", 
9298              "None          45         K           None        N                8599.01176345321                   None                                           10498.7013581079                   None                                           3204.93649737055                  None                                          4436.14046641897                  None                                          5313.74138343704                  None                                          6415.86177652694                  None                                          8546.79665373249                   None                                           9587.16245449134                   None                                           11322.2529042385                   None                                           6797.53838612575                  None                                          13745.1536613763                   None                                           11967.5433300612                  None                                          30890.8603419261                   None                                           61730.6213936947                   None                                       \n", 
9299              "None          46         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9300              "None          48         T           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9301              "None          49         A           None        N                9279.63849130869                   None                                           11063.0654625247                   None                                           4737.11992391463                  None                                          5643.40583860235                  None                                          6356.45614406507                  None                                          7302.87406141381                  None                                          8459.17105047661                   None                                           8761.54554569995                   None                                           10632.2343488142                   None                                           5572.92782399155                  None                                          12102.1714908775                   None                                           10037.6988885228                  None                                          28806.6916858172                   None                                           59579.0348769179                   None                                       \n", 
9302              "None          50         K           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9303              "None          51         Y           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9304              "None          52         V           None        N                8704.45610117774                   None                                           10585.2389163429                   None                                            3477.9549539207                  None                                          4637.22923167743                  None                                          5482.73656118686                  None                                           6556.5108895527                  None                                          8481.06470969555                   None                                           9372.86414918436                   None                                           11141.3782476763                   None                                           6491.79686536093                  None                                          13378.2843939736                   None                                           11544.3205736882                  None                                            30440.62308788                   None                                           61266.7742546508                   None                                       \n", 
9305              "None          53         A           None        N                9497.02860450276                   None                                           11246.0339326126                   None                                           5149.96766581255                  None                                          5994.15475647208                  None                                          6669.81232845336                  None                                          7577.19152075731                  None                                          8516.77431951689                   None                                           8639.36099840319                   None                                           10531.7750336522                   None                                           5378.79193153767                  None                                          11752.8060152439                   None                                           9613.59939949642                  None                                          28334.9153747994                   None                                           59090.2988815445                   None                                       \n", 
9306              "None          54         N           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9307              "None          55         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9308              "None          57         G           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9309              "None          58         M           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n", 
9310              "None          59         Q           None        N            None                                   None                                       None                                   None                                       None                                  None                                      None                                  None                                      None                                  None                                      None                                  None                                      None                                   None                                       None                                   None                                       None                                   None                                       None                                  None                                      None                                   None                                       None                                  None                                      None                                   None                                       None                                   None                                       \n" 
9311          ] 
9312          # Check the created w_eff file. 
9313          lines = w_eff_file.readlines() 
9314          for i in range(len(lines)): 
9315              # Test lines starting with # 
9316              if w_eff_result[i][0] == "#": 
9317                  self.assertEqual(w_eff_result[i], lines[i]) 
9318              # If the line is equal each other, make a line comparison. This should catch lines with None values. 
9319              if w_eff_result[i] == lines[i]: 
9320                  self.assertEqual(w_eff_result[i], lines[i]) 
9321              # If the line is not equal each other, make a slower comparison of values. 
9322              else: 
9323                  # Print lines if they don't match. To help find differences. 
9324                  print(w_eff_result[i]) 
9325                  print(lines[i]) 
9326   
9327                  # First test first 62 characters containing spin information 
9328                  self.assertEqual(w_eff_result[i][:62], lines[i][:62]) 
9329   
9330                  # Make a string split after 62 characters. Select each second element, so None values are skipped. 
9331                  w_eff_result_s = w_eff_result[i][62:].split()[::2] 
9332                  print(w_eff_result_s ) 
9333                  lines_s = lines[i][62:].split()[::2] 
9334                  print(lines_s) 
9335                  # Loop over the value elements 
9336                  for j in range(len(lines_s)): 
9337                      print(w_eff_result_s[j], lines_s[j]) 
9338                      # Assume a precision to digits. 
9339                      self.assertAlmostEqual(float(w_eff_result_s[j]), float(lines_s[j]), 14) 
9340   
9341          # Close file 
9342          w_eff_file.close() 
9343   
9344   
9345 -    def verify_estimate_r2eff_err_compare_mc(self): 
9346          """Test the user function for estimating R2eff errors from exponential curve fitting, and compare it with Monte-Carlo simulations. 
9347   
9348          This follows Task 7822. 
9349          U{task #7822<https://gna.org/task/index.php?7822>}: Implement user function to estimate R2eff and associated errors for exponential curve fitting. 
9350   
9351          This uses the data from Kjaergaard's paper at U{DOI: 10.1021/bi4001062<http://dx.doi.org/10.1021/bi4001062>}. 
9352          Optimisation of the Kjaergaard et al., 2013 Off-resonance R1rho relaxation dispersion experiments using the 'DPL' model. 
9353          """ 
9354   
9355          # Load the data. 
9356          data_path = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'Kjaergaard_et_al_2013'+sep 
9357   
9358          # Set pipe name, bundle and type. 
9359          pipe_name = 'base pipe' 
9360          pipe_bundle = 'relax_disp' 
9361          pipe_type = 'relax_disp' 
9362   
9363          # Create the data pipe. 
9364          self.interpreter.pipe.create(pipe_name=pipe_name, bundle=pipe_bundle, pipe_type=pipe_type) 
9365   
9366          file = data_path + '1_setup_r1rho_GUI.py' 
9367          self.interpreter.script(file=file, dir=None) 
9368   
9369          # Deselect all spins. 
9370          self.interpreter.deselect.spin(spin_id=':1-100', change_all=False) 
9371   
9372          # Select one spin. 
9373          self.interpreter.select.spin(spin_id=':52@N', change_all=False) 
9374   
9375          # Set the model. 
9376          self.interpreter.relax_disp.select_model(MODEL_R2EFF) 
9377   
9378          # Check if intensity errors have already been calculated. 
9379          check_intensity_errors() 
9380   
9381          # Do a grid search. 
9382          self.interpreter.minimise.grid_search(lower=None, upper=None, inc=11, constraints=True, verbosity=1) 
9383   
9384          # Set algorithm. 
9385          min_algor = 'Newton' 
9386          constraints = True 
9387          if constraints: 
9388              min_options = ('%s'%(min_algor),) 
9389              #min_algor = 'Log barrier' 
9390              min_algor = 'Method of Multipliers' 
9391              scaling_matrix = assemble_scaling_matrix(scaling=True) 
9392   
9393              # Collect spins 
9394              all_spin_ids = [] 
9395              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9396                  all_spin_ids.append(spin_id) 
9397   
9398              spins = spin_ids_to_containers(all_spin_ids[:1]) 
9399   
9400              # Get constraints 
9401              A, b = linear_constraints(spins=spins, scaling_matrix=scaling_matrix[0]) 
9402          else: 
9403              min_options = () 
9404              A, b = None, None 
9405          min_options = () 
9406          sim_boot = 200 
9407          scaling_list = [1.0, 1.0] 
9408   
9409          # Minimise. 
9410          self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints, verbosity=1) 
9411   
9412          # Loop over old err attributes. 
9413          err_attr_list = ['r2eff_err', 'i0_err'] 
9414   
9415          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9416              # Loop over old err attributes. 
9417              for err_attr in err_attr_list: 
9418                  if hasattr(cur_spin, err_attr): 
9419                      delattr(cur_spin, err_attr) 
9420   
9421          # Collect the estimation data from boot. 
9422          my_dic = {} 
9423          param_key_list = [] 
9424          est_keys = [] 
9425          est_key = '-2' 
9426          est_keys.append(est_key) 
9427          spin_id_list = [] 
9428   
9429          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9430              # Add key to dic. 
9431              my_dic[spin_id] = {} 
9432   
9433              # Add key for estimate. 
9434              my_dic[spin_id][est_key] = {} 
9435   
9436              # Add spin key to list. 
9437              spin_id_list.append(spin_id) 
9438   
9439              # Generate spin string. 
9440              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9441   
9442              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9443                  # Generate the param_key. 
9444                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9445   
9446                  # Append key. 
9447                  param_key_list.append(param_key) 
9448   
9449                  # Add key to dic. 
9450                  my_dic[spin_id][est_key][param_key] = {} 
9451   
9452                  values = [] 
9453                  errors = [] 
9454                  times = [] 
9455                  for time in loop_time(exp_type=exp_type, frq=frq, offset=offset, point=point): 
9456                      values.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)) 
9457                      errors.append(average_intensity(spin=cur_spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)) 
9458                      times.append(time) 
9459   
9460                  # Convert to numpy array. 
9461                  values = asarray(values) 
9462                  errors = asarray(errors) 
9463                  times = asarray(times) 
9464   
9465                  r2eff = getattr(cur_spin, 'r2eff')[param_key] 
9466                  i0 = getattr(cur_spin, 'i0')[param_key] 
9467   
9468                  R_m_sim_l = [] 
9469                  I0_m_sim_l = [] 
9470                  for j in range(sim_boot): 
9471                      if j in range(0, 100000, 100): 
9472                          print("Simulation %i"%j) 
9473                      # Start minimisation. 
9474   
9475                      # Produce errors 
9476                      I_err = [] 
9477                      for j, error in enumerate(errors): 
9478                          I_error = gauss(values[j], error) 
9479                          I_err.append(I_error) 
9480                      # Convert to numpy array. 
9481                      I_err = asarray(I_err) 
9482   
9483                      x0 = [r2eff, i0] 
9484                      model = Relax_fit_opt(num_params=len(x0), values=I_err, errors=errors, relax_times=times, scaling_matrix=scaling_list) 
9485   
9486                      # Ref input. 
9487                      #def generic_minimise(func=None, dfunc=None, d2func=None, args=(), x0=None, min_algor=None, min_options=None, func_tol=1e-25, grad_tol=None, maxiter=1e6, A=None, b=None, l=None, u=None, c=None, dc=None, d2c=None, print_flag=0, print_prefix="", full_output=False): 
9488                      # l=l, u=u, c=c, dc=dc, d2c=d2c 
9489                      # l: Lower bound constraint vector (l <= x <= u). 
9490                      # u: Upper bound constraint vector (l <= x <= u). 
9491                      # c: User supplied constraint function. 
9492                      # dc: User supplied constraint gradient function. 
9493                      params_minfx_sim_j, chi2_minfx_sim_j, iter_count, f_count, g_count, h_count, warning = generic_minimise(func=model.func, dfunc=model.dfunc, d2func=model.d2func, args=(), x0=x0, min_algor=min_algor, min_options=min_options, A=A, b=b, full_output=True, print_flag=0) 
9494   
9495                      R_m_sim_j, I0_m_sim_j = params_minfx_sim_j 
9496                      R_m_sim_l.append(R_m_sim_j) 
9497                      I0_m_sim_l.append(I0_m_sim_j) 
9498   
9499                  # Get stats on distribution. 
9500                  sigma_R_sim = std(asarray(R_m_sim_l), ddof=1) 
9501                  sigma_I0_sim = std(asarray(I0_m_sim_l), ddof=1) 
9502                  my_dic[spin_id][est_key][param_key]['r2eff_err'] = sigma_R_sim 
9503                  my_dic[spin_id][est_key][param_key]['i0_err'] = sigma_I0_sim 
9504   
9505          # Estimate R2eff errors. 
9506          self.interpreter.relax_disp.r2eff_err_estimate() 
9507   
9508          est_key = '-1' 
9509          est_keys.append(est_key) 
9510   
9511          # Collect data. 
9512          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9513              # Add key for estimate. 
9514              my_dic[spin_id][est_key] = {} 
9515   
9516              for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9517                  # Generate the param_key. 
9518                  param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9519   
9520                  # Add key to dic. 
9521                  my_dic[spin_id][est_key][param_key] = {} 
9522   
9523                  # Get the value. 
9524                  # Loop over err attributes. 
9525                  for err_attr in err_attr_list: 
9526                      if hasattr(cur_spin, err_attr): 
9527                          get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9528                      else: 
9529                          get_err_attr = 0.0 
9530   
9531                      # Save to dic. 
9532                      my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9533   
9534   
9535          # Make Carlo Simulations number 
9536          mc_number_list = list(range(0, 1000, 250)) 
9537   
9538          sim_attr_list = ['chi2_sim', 'f_count_sim', 'g_count_sim', 'h_count_sim', 'i0_sim', 'iter_sim', 'peak_intensity_sim', 'r2eff_sim', 'select_sim', 'warning_sim'] 
9539   
9540          # Loop over the Monte Carlo simulations: 
9541          for number in mc_number_list: 
9542              # First delete old simulations. 
9543              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9544                  # Loop over old err attributes. 
9545                  for err_attr in err_attr_list: 
9546                      if hasattr(cur_spin, err_attr): 
9547                          delattr(cur_spin, err_attr) 
9548   
9549                  # Loop over the simulated attributes. 
9550                  for sim_attr in sim_attr_list: 
9551                      if hasattr(cur_spin, sim_attr): 
9552                          delattr(cur_spin, sim_attr) 
9553   
9554              self.interpreter.monte_carlo.setup(number=number) 
9555              self.interpreter.monte_carlo.create_data() 
9556              self.interpreter.monte_carlo.initial_values() 
9557              self.interpreter.minimise.execute(min_algor=min_algor, constraints=constraints) 
9558              self.interpreter.eliminate() 
9559              self.interpreter.monte_carlo.error_analysis() 
9560   
9561              est_key = '%i'%number 
9562              est_keys.append(est_key) 
9563   
9564              # Collect data. 
9565              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9566                  # Add key for estimate. 
9567                  my_dic[spin_id][est_key] = {} 
9568   
9569                  for exp_type, frq, offset, point, ei, mi, oi, di in loop_exp_frq_offset_point(return_indices=True): 
9570                      # Generate the param_key. 
9571                      param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point) 
9572   
9573                      # Add key to dic. 
9574                      my_dic[spin_id][est_key][param_key] = {} 
9575   
9576                      # Get the value. 
9577                      # Loop over err attributes. 
9578                      for err_attr in err_attr_list: 
9579                          if hasattr(cur_spin, err_attr): 
9580                              get_err_attr = getattr(cur_spin, err_attr)[param_key] 
9581                          else: 
9582                              get_err_attr = 0.0 
9583   
9584                          # Save to dic. 
9585                          my_dic[spin_id][est_key][param_key][err_attr] = get_err_attr 
9586   
9587          # Set what to extract. 
9588          err_attr = err_attr_list[0] 
9589   
9590          # Define list with text. 
9591          text_list = [] 
9592   
9593          # Now loop through the data. 
9594          for spin_id in spin_id_list: 
9595              for est_key in est_keys: 
9596                  # Define list to pickup data. 
9597                  r2eff_err_list = [] 
9598   
9599                  for param_key in param_key_list: 
9600                      # Get the value. 
9601                      r2eff_err = my_dic[spin_id][est_key][param_key][err_attr] 
9602   
9603                      # Add to list. 
9604                      r2eff_err_list.append(r2eff_err) 
9605   
9606                  # Sum the list 
9607                  sum_array = sum(array(r2eff_err_list)) 
9608   
9609                  # Join floats to string. 
9610                  r2eff_err_str = " ".join(format(x, "2.3f") for x in r2eff_err_list) 
9611   
9612                  # Define print string. 
9613                  text = "%8s %s sum= %2.3f" % (est_key, r2eff_err_str, sum_array) 
9614                  text_list.append(text) 
9615   
9616   
9617          # Now print. 
9618          filepath = NamedTemporaryFile(delete=False).name 
9619          # Open the files for testing. 
9620          w_file = open(filepath, 'w') 
9621   
9622          print("Printing the estimated R2eff error as function of estimation from Co-variance and number of Monte-Carlo simulations.") 
9623   
9624          for text in text_list: 
9625              # Print. 
9626              print(text) 
9627   
9628              # Write to file. 
9629              w_file.write(text+"\n") 
9630   
9631          # Close files 
9632          w_file.close() 
9633   
9634          print("Filepath is: %s"%filepath) 
9635          print("Start 'gnuplot' and write:") 
9636          print("set term dumb") 
9637          print("plot '%s' using 1:17 title 'R2eff error as function of MC number' w linespoints "%filepath) 
9638   
9639   
9640 -    def verify_r1rho_kjaergaard_missing_r1(self, models=None, result_dir_name=None, r2eff_estimate=None): 
9641          """Verification of test_r1rho_kjaergaard_missing_r1.""" 
9642   
9643          # Check the kex value of residue 52 
9644          #self.assertAlmostEqual(cdp.mol[0].res[41].spin[0].kex, ds.ref[':52@N'][6]) 
9645   
9646          # Print results for each model. 
9647          print("\n\n################") 
9648          print("Printing results") 
9649          print("################\n") 
9650          for model in models: 
9651              # Skip R2eff model. 
9652              if model == MODEL_R2EFF: 
9653                  continue 
9654   
9655              # Switch to pipe. 
9656              self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9657              print("\nModel: %s" % (model)) 
9658   
9659              # Loop over the spins. 
9660              for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9661                  # Generate spin string. 
9662                  spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9663   
9664                  # Loop over the parameters. 
9665                  print("Optimised parameters for spin: %s" % (spin_string)) 
9666                  for param in cur_spin.params + ['chi2']: 
9667                      # Get the value. 
9668                      if param in ['r1', 'r2']: 
9669                          for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True): 
9670                              # Generate the R20 key. 
9671                              r20_key = generate_r20_key(exp_type=exp_type, frq=frq) 
9672   
9673                              # Get the value. 
9674                              value = getattr(cur_spin, param)[r20_key] 
9675   
9676                              # Print value. 
9677                              print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9678   
9679                              # Compare values. 
9680                              if spin_id == ':52@N': 
9681                                  if param == 'r1': 
9682                                      if model == MODEL_NOREX: 
9683                                          if r2eff_estimate == 'direct': 
9684                                              self.assertAlmostEqual(value, 1.46138805) 
9685                                          elif r2eff_estimate == 'MC2000': 
9686                                              self.assertAlmostEqual(value, 1.46328102) 
9687                                          elif r2eff_estimate == 'chi2_pyt': 
9688                                              self.assertAlmostEqual(value, 1.43820629) 
9689                                      elif model == MODEL_DPL94: 
9690                                          if r2eff_estimate == 'direct': 
9691                                              self.assertAlmostEqual(value, 1.44845742) 
9692                                          elif r2eff_estimate == 'MC2000': 
9693                                              self.assertAlmostEqual(value, 1.45019848) 
9694                                          elif r2eff_estimate == 'chi2_pyt': 
9695                                              self.assertAlmostEqual(value, 1.44666512) 
9696                                      elif model == MODEL_TP02: 
9697                                          if r2eff_estimate == 'direct': 
9698                                              self.assertAlmostEqual(value, 1.54354392) 
9699                                          elif r2eff_estimate == 'MC2000': 
9700                                              self.assertAlmostEqual(value, 1.54352369) 
9701                                          elif r2eff_estimate == 'chi2_pyt': 
9702                                              self.assertAlmostEqual(value, 1.55964020) 
9703                                      elif model == MODEL_TAP03: 
9704                                          if r2eff_estimate == 'direct': 
9705                                              self.assertAlmostEqual(value, 1.54356410) 
9706                                          elif r2eff_estimate == 'MC2000': 
9707                                              self.assertAlmostEqual(value, 1.54354367) 
9708                                          elif r2eff_estimate == 'chi2_pyt': 
9709                                              self.assertAlmostEqual(value, 1.55967157) 
9710                                      elif model == MODEL_MP05: 
9711                                          if r2eff_estimate == 'direct': 
9712                                              self.assertAlmostEqual(value, 1.54356416) 
9713                                          elif r2eff_estimate == 'MC2000': 
9714                                              self.assertAlmostEqual(value, 1.54354372) 
9715                                          elif r2eff_estimate == 'chi2_pyt': 
9716                                              self.assertAlmostEqual(value, 1.55967163) 
9717                                      elif model == MODEL_NS_R1RHO_2SITE: 
9718                                          if r2eff_estimate == 'direct': 
9719                                              self.assertAlmostEqual(value, 1.41359221, 5) 
9720                                          elif r2eff_estimate == 'MC2000': 
9721                                              self.assertAlmostEqual(value, 1.41321968, 5) 
9722                                          elif r2eff_estimate == 'chi2_pyt': 
9723                                              self.assertAlmostEqual(value, 1.36303129, 5) 
9724   
9725                                  elif param == 'r2': 
9726                                      if model == MODEL_NOREX: 
9727                                          if r2eff_estimate == 'direct': 
9728                                              self.assertAlmostEqual(value, 11.48392439) 
9729                                          elif r2eff_estimate == 'MC2000': 
9730                                              self.assertAlmostEqual(value, 11.48040934) 
9731                                          elif r2eff_estimate == 'chi2_pyt': 
9732                                              self.assertAlmostEqual(value, 11.47224488) 
9733                                      elif model == MODEL_DPL94: 
9734                                          if r2eff_estimate == 'direct': 
9735                                              self.assertAlmostEqual(value, 10.15688372, 6) 
9736                                          elif r2eff_estimate == 'MC2000': 
9737                                              self.assertAlmostEqual(value, 10.16304887, 6) 
9738                                          elif r2eff_estimate == 'chi2_pyt': 
9739                                              self.assertAlmostEqual(value, 9.20037797, 6) 
9740                                      elif model == MODEL_TP02: 
9741                                          if r2eff_estimate == 'direct': 
9742                                              self.assertAlmostEqual(value, 9.72654896, 6) 
9743                                          elif r2eff_estimate == 'MC2000': 
9744                                              self.assertAlmostEqual(value, 9.72772726, 6) 
9745                                          elif r2eff_estimate == 'chi2_pyt': 
9746                                              self.assertAlmostEqual(value, 9.53948340, 6) 
9747                                      elif model == MODEL_TAP03: 
9748                                          if r2eff_estimate == 'direct': 
9749                                              self.assertAlmostEqual(value, 9.72641887, 6) 
9750                                          elif r2eff_estimate == 'MC2000': 
9751                                              self.assertAlmostEqual(value, 9.72759374, 6) 
9752                                          elif r2eff_estimate == 'chi2_pyt': 
9753                                              self.assertAlmostEqual(value, 9.53926913, 6) 
9754                                      elif model == MODEL_MP05: 
9755                                          if r2eff_estimate == 'direct': 
9756                                              self.assertAlmostEqual(value, 9.72641723, 6) 
9757                                          elif r2eff_estimate == 'MC2000': 
9758                                              self.assertAlmostEqual(value, 9.72759220, 6) 
9759                                          elif r2eff_estimate == 'chi2_pyt': 
9760                                              self.assertAlmostEqual(value, 9.53926778, 6) 
9761                                      elif model == MODEL_NS_R1RHO_2SITE: 
9762                                          if r2eff_estimate == 'direct': 
9763                                              self.assertAlmostEqual(value, 9.34531535, 5) 
9764                                          elif r2eff_estimate == 'MC2000': 
9765                                              self.assertAlmostEqual(value, 9.34602793, 5) 
9766                                          elif r2eff_estimate == 'chi2_pyt': 
9767                                              self.assertAlmostEqual(value, 9.17631409, 5) 
9768   
9769                      # For all other parameters. 
9770                      else: 
9771                          # Get the value. 
9772                          value = getattr(cur_spin, param) 
9773   
9774                          # Print value. 
9775                          print("%-10s %-6s %-6s %3.8f" % ("Parameter:", param, "Value:", value)) 
9776   
9777                          # Compare values. 
9778                          if spin_id == ':52@N': 
9779                              if param == 'phi_ex': 
9780                                  if model == MODEL_DPL94: 
9781                                      if r2eff_estimate == 'direct': 
9782                                          self.assertAlmostEqual(value, 0.07599563) 
9783                                      elif r2eff_estimate == 'MC2000': 
9784                                          self.assertAlmostEqual(value, 0.07561937) 
9785                                      elif r2eff_estimate == 'chi2_pyt': 
9786                                          self.assertAlmostEqual(value, 0.12946061) 
9787   
9788                              elif param == 'pA': 
9789                                  if model == MODEL_TP02: 
9790                                      if r2eff_estimate == 'direct': 
9791                                          self.assertAlmostEqual(value, 0.88827040) 
9792                                      elif r2eff_estimate == 'MC2000': 
9793                                          self.assertAlmostEqual(value, 0.88807487) 
9794                                      elif r2eff_estimate == 'chi2_pyt': 
9795                                          self.assertAlmostEqual(value, 0.87746233) 
9796                                  elif model == MODEL_TAP03: 
9797                                      if r2eff_estimate == 'direct': 
9798                                          self.assertAlmostEqual(value, 0.88828922) 
9799                                      elif r2eff_estimate == 'MC2000': 
9800                                          self.assertAlmostEqual(value, 0.88809318) 
9801                                      elif r2eff_estimate == 'chi2_pyt': 
9802                                          self.assertAlmostEqual(value, 0.87747558) 
9803                                  elif model == MODEL_MP05: 
9804                                      if r2eff_estimate == 'direct': 
9805                                          self.assertAlmostEqual(value, 0.88828924, 6) 
9806                                      elif r2eff_estimate == 'MC2000': 
9807                                          self.assertAlmostEqual(value, 0.88809321) 
9808                                      elif r2eff_estimate == 'chi2_pyt': 
9809                                          self.assertAlmostEqual(value, 0.87747562) 
9810                                  elif model == MODEL_NS_R1RHO_2SITE: 
9811                                      if r2eff_estimate == 'direct': 
9812                                          self.assertAlmostEqual(value, 0.94504369, 6) 
9813                                      elif r2eff_estimate == 'MC2000': 
9814                                          self.assertAlmostEqual(value, 0.94496541, 6) 
9815                                      elif r2eff_estimate == 'chi2_pyt': 
9816                                          self.assertAlmostEqual(value, 0.92084707, 6) 
9817   
9818                              elif param == 'dw': 
9819                                  if model == MODEL_TP02: 
9820                                      if r2eff_estimate == 'direct': 
9821                                          self.assertAlmostEqual(value, 1.08875840, 6) 
9822                                      elif r2eff_estimate == 'MC2000': 
9823                                          self.assertAlmostEqual(value, 1.08765638, 6) 
9824                                      elif r2eff_estimate == 'chi2_pyt': 
9825                                          self.assertAlmostEqual(value, 1.09753230, 6) 
9826                                  elif model == MODEL_TAP03: 
9827                                      if r2eff_estimate == 'direct': 
9828                                          self.assertAlmostEqual(value, 1.08837238, 6) 
9829                                      elif r2eff_estimate == 'MC2000': 
9830                                          self.assertAlmostEqual(value, 1.08726698, 6) 
9831                                      elif r2eff_estimate == 'chi2_pyt': 
9832                                          self.assertAlmostEqual(value, 1.09708821, 6) 
9833                                  elif model == MODEL_MP05: 
9834                                      if r2eff_estimate == 'direct': 
9835                                          self.assertAlmostEqual(value, 1.08837241, 6) 
9836                                      elif r2eff_estimate == 'MC2000': 
9837                                          self.assertAlmostEqual(value, 1.08726706, 6) 
9838                                      elif r2eff_estimate == 'chi2_pyt': 
9839                                          self.assertAlmostEqual(value, 1.09708832, 6) 
9840                                  elif model == MODEL_NS_R1RHO_2SITE: 
9841                                      if r2eff_estimate == 'direct': 
9842                                          self.assertAlmostEqual(value, 1.56001812, 5) 
9843                                      elif r2eff_estimate == 'MC2000': 
9844                                          self.assertAlmostEqual(value, 1.55833321, 5) 
9845                                      elif r2eff_estimate == 'chi2_pyt': 
9846                                          self.assertAlmostEqual(value, 1.36406712, 5) 
9847   
9848                              elif param == 'kex': 
9849                                  if model == MODEL_DPL94: 
9850                                      if r2eff_estimate == 'direct': 
9851                                          self.assertAlmostEqual(value/1e5, 4460.43711569/1e5, 7) 
9852                                      elif r2eff_estimate == 'MC2000': 
9853                                          self.assertAlmostEqual(value/1e5, 4419.03917195/1e5, 7) 
9854                                      elif r2eff_estimate == 'chi2_pyt': 
9855                                          self.assertAlmostEqual(value/1e5, 6790.22736344/1e5, 7) 
9856                                  elif model == MODEL_TP02: 
9857                                      if r2eff_estimate == 'direct': 
9858                                          self.assertAlmostEqual(value/1e5, 4921.28602757/1e5, 7) 
9859                                      elif r2eff_estimate == 'MC2000': 
9860                                          self.assertAlmostEqual(value/1e5, 4904.70144883/1e5, 7) 
9861                                      elif r2eff_estimate == 'chi2_pyt': 
9862                                          self.assertAlmostEqual(value/1e5, 5146.20306591/1e5, 7) 
9863                                  elif model == MODEL_TAP03: 
9864                                      if r2eff_estimate == 'direct': 
9865                                          self.assertAlmostEqual(value/1e5, 4926.42963491/1e5, 7) 
9866                                      elif r2eff_estimate == 'MC2000': 
9867                                          self.assertAlmostEqual(value/1e5, 4909.86877150/1e5, 7) 
9868                                      elif r2eff_estimate == 'chi2_pyt': 
9869                                          self.assertAlmostEqual(value/1e5, 5152.51105814/1e5, 7) 
9870                                  elif model == MODEL_MP05: 
9871                                      if r2eff_estimate == 'direct': 
9872                                          self.assertAlmostEqual(value/1e5, 4926.44236315/1e5, 7) 
9873                                      elif r2eff_estimate == 'MC2000': 
9874                                          self.assertAlmostEqual(value/1e5, 4909.88110195/1e5, 7) 
9875                                      elif r2eff_estimate == 'chi2_pyt': 
9876                                          self.assertAlmostEqual(value/1e5, 5152.52097111/1e5, 7) 
9877                                  elif model == MODEL_NS_R1RHO_2SITE: 
9878                                      if r2eff_estimate == 'direct': 
9879                                          self.assertAlmostEqual(value/1e5, 5628.66061488/1e5, 6) 
9880                                      elif r2eff_estimate == 'MC2000': 
9881                                          self.assertAlmostEqual(value/1e5, 5610.20221435/1e5, 6) 
9882                                      elif r2eff_estimate == 'chi2_pyt': 
9883                                          self.assertAlmostEqual(value/1e5, 5643.34067090/1e5, 6) 
9884   
9885                              elif param == 'chi2': 
9886                                  if model == MODEL_NOREX: 
9887                                      if r2eff_estimate == 'direct': 
9888                                          self.assertAlmostEqual(value, 848.42016907, 5) 
9889                                      elif r2eff_estimate == 'MC2000': 
9890                                          self.assertAlmostEqual(value, 3363.95829122, 5) 
9891                                      elif r2eff_estimate == 'chi2_pyt': 
9892                                          self.assertAlmostEqual(value, 5976.49946726, 5) 
9893                                  elif model == MODEL_DPL94: 
9894                                      if r2eff_estimate == 'direct': 
9895                                          self.assertAlmostEqual(value, 179.47041241) 
9896                                      elif r2eff_estimate == 'MC2000': 
9897                                          self.assertAlmostEqual(value, 710.24767560) 
9898                                      elif r2eff_estimate == 'chi2_pyt': 
9899                                          self.assertAlmostEqual(value, 612.72616697, 5) 
9900                                  elif model == MODEL_TP02: 
9901                                      if r2eff_estimate == 'direct': 
9902                                          self.assertAlmostEqual(value, 29.33882530, 6) 
9903                                      elif r2eff_estimate == 'MC2000': 
9904                                          self.assertAlmostEqual(value, 114.47142772, 6) 
9905                                      elif r2eff_estimate == 'chi2_pyt': 
9906                                          self.assertAlmostEqual(value, 250.50838162, 5) 
9907                                  elif model == MODEL_TAP03: 
9908                                      if r2eff_estimate == 'direct': 
9909                                          self.assertAlmostEqual(value, 29.29050673, 6) 
9910                                      elif r2eff_estimate == 'MC2000': 
9911                                          self.assertAlmostEqual(value, 114.27987534) 
9912                                      elif r2eff_estimate == 'chi2_pyt': 
9913                                          self.assertAlmostEqual(value, 250.04050719, 5) 
9914                                  elif model == MODEL_MP05: 
9915                                      if r2eff_estimate == 'direct': 
9916                                          self.assertAlmostEqual(value, 29.29054301, 6) 
9917                                      elif r2eff_estimate == 'MC2000': 
9918                                          self.assertAlmostEqual(value, 114.28002272) 
9919                                      elif r2eff_estimate == 'chi2_pyt': 
9920                                          self.assertAlmostEqual(value, 250.04077478, 5) 
9921                                  elif model == MODEL_NS_R1RHO_2SITE: 
9922                                      if r2eff_estimate == 'direct': 
9923                                          self.assertAlmostEqual(value, 34.44010543, 6) 
9924                                      elif r2eff_estimate == 'MC2000': 
9925                                          self.assertAlmostEqual(value, 134.14368365) 
9926                                      elif r2eff_estimate == 'chi2_pyt': 
9927                                          self.assertAlmostEqual(value, 278.55121388, 5) 
9928   
9929   
9930          # Print the final pipe. 
9931          model = 'final' 
9932          self.interpreter.pipe.switch(pipe_name='%s - relax_disp' % (model)) 
9933          print("\nFinal pipe") 
9934   
9935          # Loop over the spins. 
9936          for cur_spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True): 
9937              # Generate spin string. 
9938              spin_string = generate_spin_string(spin=cur_spin, mol_name=mol_name, res_num=resi, res_name=resn) 
9939   
9940              # Loop over the parameters. 
9941              print("Optimised model for spin: %s" % (spin_string)) 
9942              param = 'model' 
9943   
9944              # Get the value. 
9945              value = getattr(cur_spin, param) 
9946              print("%-10s %-6s %-6s %6s" % ("Parameter:", param, "Value:", value)) 
9947   
9948   
9949          ### Now check some of the written out files. 
9950          file_names = ['r1rho_prime', 'r1'] 
9951   
9952          for file_name_i in file_names: 
9953   
9954              # Make the file name. 
9955              file_name = "%s.out" % file_name_i 
9956   
9957              # Get the file path. 
9958              file_path = get_file_path(file_name, result_dir_name + sep + model) 
9959   
9960              # Test the file exists. 
9961              print("Testing file access to: %s"%file_path) 
9962              self.assert_(access(file_path, F_OK)) 
9963   
9964              # Now open, and compare content, line by line. 
9965              file_prod = open(file_path) 
9966              lines_prod = file_prod.readlines() 
9967              file_prod.close() 
9968   
9969              # Loop over the lines. 
9970              for i, line in enumerate(lines_prod): 
9971                  # Make the string test 
9972                  line_split = line.split() 
9973   
9974                  # Continue for comment lines. 
9975                  if line_split[0] == "#": 
9976                      print(line), 
9977                      continue 
9978   
9979                  # Assign the split of the line. 
9980                  mol_name, res_num, res_name, spin_num, spin_name, val, sd_error = line_split 
9981                  print(mol_name, res_num, res_name, spin_num, spin_name, val, sd_error) 
9982   
9983                  if res_num == '52': 
9984                      # Assert that the value is not None. 
9985                      self.assertNotEqual(val, 'None') 
9986